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Intel to give Intel Foundry more independence, expands AWS partnership

Intel to give Intel Foundry more independence, expands AWS partnership

Intel plans to establish its Foundry business as an independent subsidiary as it aims to cut costs and optimize its business.

The move, outlined in a letter from Intel CEO Pat Gelsinger, came after a day of news aimed at calming fears about the x86 chip giant's future.

Intel also announced an expanded partnership with Amazon Web Services for custom chip designs. Intel Foundry will produce an AI fabric chip for AWS on the Intel 18A architecture as well as a custom Xeon 6 chip for AWS. The two companies will work on other chip designs going forward.

That AWS partnership comes as Intel was awarded $3 billion in direct funding under the CHIPS and Science Act for the U.S. government's Secure Enclave program.

The takeaway from the AWS and CHIPS and Science Act award is that Intel Foundry has a pipeline. For Intel, the issue with Intel Foundry is that manufacturing requires a lot of cash. Intel is trying cut about $10 billion in costs amid competition from AMD and Nvidia.

Gelsinger said that Intel is "more than halfway" through the process of cutting 15,000 jobs by the end of the year. Employees will be notified in mid-October. Intel is also cutting about two-thirds of its real estate footprint by the end of the year.

By making Intel Foundry a subsidiary, Intel stopped short of a complete spin-off, but noted that the structure "provides our external foundry customers and suppliers with clearer separation and independence from the rest of Intel," said Gelsinger. Intel Foundry will also be able to find independent sources of funding and capital structure.

As for Intel the chip design and product company, Gelsinger said the plan is to maximize its x86 architecture for AI across PCs, edge devices and data center. The focus will be on AI inference workloads.

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Microsoft outlines Copilot agents for enterprises

Microsoft outlines Copilot agents for enterprises

Microsoft said Copilot agents are generally available in a move that provides enterprises agentic AI to automate business processes while preserving that Copilot brand it's known for.

In a blog post aimed at Salesforce's Dreamforce 2024 conference, Microsoft said it will add agent builder to Copilot Studio. Copilot agents are designed to be fully autonomous and run in the background to carry out tasks.

With Salesforce push, AI Agents, agentic AI overload looms

Microsoft said Copilot agents can be created in BizChat or SharePoint and then mentioned in various apps such as Teams or Outlook. Copilot agents and agent builder in BizChat will roll out in the weeks ahead with SharePoint agent builder in preview in October.

Most enterprises vendors have positioned agents to be a different more advanced version of copilots. Salesforce CEO Marc Benioff recently outlined Agentforce and said the platform will be the un-Copilot. "So many customers are so disappointed in what they bought from Microsoft Copilot because they're not getting the accuracy and the response that they want. Microsoft has disappointed so many customers with AI," Benioff said.

Microsoft will beg to differ--especially since it rolled out numerous Copilot enhancements even with its AI agent announcements.

Constellation Research analyst Holger Mueller said Microsoft has an interesting Copilot vs. agents line to walk.

"Microsoft tries to get in its agents before Salesforce.

Microsoft keeps pushing for agents, and interestingly agents are there to help Copilots, which fits the Microsoft vision, but does not address the Copilot inflation that Microsoft users are battling with day in and day out. Microsoft will have to create an uber AI persona. Maybe it will be the comeback of Cortana?"

In the meantime, Microsoft announced a bevy of enhancements for Microsoft 365 Copilot including:

  • Copilot Pages, a collaboration canvas for multiple AI copilots. Microsoft is pitching Copilot Pages as a way to turn genAI artifacts and make them reusable with the ability to edit, add and share AI generated content.
  • Copilot in Excel is generally available and Copilot in Excel with Python is in public preview.
  • Copilot on PowerPoint with Narrative builder is generally available as is Brand manager to ensure presentations are on brand.
  • Copilot in Teams will combine meeting transcripts and chats to provide a complete picture of the meeting.
  • Copilot in Outlook will prioritize emails and messages with a concise summary.
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Salesforce adds AI agents to Marketing, Commerce Clouds, Slack at Dreamforce 2024

Salesforce adds AI agents to Marketing, Commerce Clouds, Slack at Dreamforce 2024

Salesforce rolled out Agentforce additions across its Marketing and Commerce Clouds as well as Slack as it harmonizes its platform with AI agents. Salesforce's clouds, Marketing Cloud, Commerce Cloud, Service Cloud and Revenue Cloud will also work natively together.

On Friday, Salesforce outlined its Agentforce efforts, agentic AI agents that will work across the company's unified platform. The technology behind Agentforce was acquired in last year's Airkit.ai purchase. Dreamforce 2024 this week will be focused on showing what Agentforce can do.

With Agentforce, Salesforce is hitting an ongoing theme across enterprise software. Simply put, the AI agent bandwagon is about to get crowded.

Here's a look at Saleforce's platform and stack.

And the Dreamforce updates:

Commerce Cloud

Commerce Cloud gets a unified experience as it now runs on one single platform. Salesforce added that it will also add autonomous Agentforce Agents for merchants, buyers and shoppers. The Commerce Cloud updates are designed to appeal for B2C, direct to consumer and B2B commerce.

A look at the Agentforce agents, which are grounded in Data Cloud and can manage product recommendations and order lookups without human intervention:

  • Merchant aims to assist ecommerce merchandisers with promotions, site setup, goal setting, product descriptions and insights.
  • Buyer will help buyers find products, purchase and track orders via chat or portals.
  • Personal Shopper acts as a concierge on ecommerce sites.

Agentforce Merchant will be generally available in October with Personal Shopper and Buyer in beta.

The AI agents are the headliner, but Salesforce also added a series of new features to Commerce Cloud including In-Store Inventory Planning, Buy with Prime, and an enhanced Salesforce Checkout.

Salesforce also said it has expanded its partnership with Stripe to expand Salesforce Payments and express checkout methods. Customers will be able to connect their own Stripe accounts to Salesforce Payments in February.

Marketing Cloud

Salesforce said it will launch a new addition of Marketing Cloud with AI capabilities. Marketing Cloud Advanced will be able to connect marketing efforts across sales, service and commerce workflows.

Marketing Cloud Advanced includes:

  • Agentforce personalization in multiple languages.
  • Automation across teams with Salesforce Flow.
  • Unified SMS conversations across Marketing, Commerce and Service clouds.

Agentforce for Marketing will get Campaign Optimizer automates, analyzes, generates and optimizes marketing campaigns. Agentforce will also personalize engagement by customer.

Einstein Marketing Intelligence will also be a one-stop dashboard to manage and optimize campaign performance with automated data prep, transparency into budgets and integration with Tableau to visualize performance.

Tableau will be able to provide insights for every agent and app with a new Data Cloud semantic layer. Additions will feature unified apps and marketplace, drag and drop VizQL visualization and shareable semantic models and metrics.

Slack

Salesforce launched Agentforce in Slack with a new interface that enables conversations to include insights, data and actions.

In addition, Slack will get integration with third-party AI agents from Adobe, Anthropic, Cohere and Perplexity.

Salesforce is also adding channels so Salesforce CRM can be tied to records in Slack conversations.

Other items include:

  • Slack AI will have huddle notes, and simplified automation experience.
  • Slack will get collections of templates, canvases and workflows for channels.
  • Agentforce will pull in CRM insights directly into Slack.
  • Amazon Q Business will also be integrated with Slack as will Asana, Box and Workday.
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With Salesforce push, AI Agents, agentic AI overload looms

With Salesforce push, AI Agents, agentic AI overload looms

Generative AI has been the topic du jour for more than 18 months, but now the baton is going to be handed to agentic AI if Salesforce and other enterprise technology giants have their way.

Salesforce’s Dreamforce conference will be all about AI agents—known as Agentforce—and the company has had a steady drumbeat of news leading up to its flagship conference. Salesforce’s plan is to use Dreamforce to show you what Agentforce can do and reinvent the company as a platform that drives value.

The problem: Salesforce had to move early on its Agentforce news because the AI agent bandwagon was filling up so rapidly. Indeed, ServiceNow has been talking AI agents for months and its Xanadu release of its Now Platform puts agents into production this week. Oracle’s CloudWorld conference this week also included a hefty dose of AI agents across its platform, applications and cloud services. Google Cloud CEO Thomas Kurian also talked about how the company is monetizing its agents.

Speaking of monetization, Salesforce said that Agentforce will run $2 per conversation without volume discounts. To Benioff, the $2 per conversation model is a no brainer since the returns on investment are there. We’ll find out if enterprises agree.

This post first appeared in the Constellation Insight newsletter, which features bespoke content weekly and is brought to you by Hitachi Vantara.

"Dreamforce is really becoming Agentforce," said Salesforce CEO Marc Benioff. "I think this is going to be a moment that everyone is going to have to see in person to understand what is going on.” Salesforce’s plan is to outline Agentforce and then outline a bevy of customers using the technology, which was acquired in the tuck-in Airkit.ai purchase a year ago.

In 2024, AI agents came into their own as SaaS providers all worked to make generative AI use cases drive value. Presumably, enterprises will move more genAI pilots to production with the help of agents that can make decisions and automate processes on your behalf. Enter agentic AI.

The term agentic was most likely cribbed by the tech sector from psychologist Albert Bandura, a professor of social science in psychology at Stanford, who died in 2021. In 2001, Bandura wrote Social cognitive theory: An agentic perspective. Annual review of psychology 52. The term agentic has been applied to multiple fields from psychology to education to healthcare to business to portfolio management.

The rough idea behind agentic AI is to create models that can make decisions and act on your behalf. Agents are further along on the genAI progression.

Salesforce is the latest in popularizing agents, but the concept isn’t necessarily in 2024. Enterprise technology companies have been talking up AI agents for most of the year and the term has been floating around for a few years. It’s just now that venture capital will flow into agentic AI in a big way. UIPath CEO Daniel Dines said recent earnings conference call: “To me, an AI agent is basically a robot, if you want, that has some more new skills. And I think there will be multiple type of agents,” said Dines.

In fact, a new category is emerging with purpose-built AI agents for common business use cases. Constellation Research recently published a new ShortList for AI-Powered Virtual SDR Agents – which includes seven startups (and Salesforce) who have emerged with AI agent tools. While big players are getting into the game, smaller players like Qualified are showing promise with their agent roadmaps. Qualified recently added significant email capabilities to its previously chat-only AI SDR this past week.

“You are going to see almost every CRM and CX vendor offering some sort of AI-powered agent tool within the next year or so,” notes Constellation Vice President & Principal Analyst Martin Schneider. “It is the natural evolution from co-pilots; shifting from prompt-based points of insight to semi-autonomous agents that can take action and further along key – yet typically safer or mundane – processes. It is about expanding reach, productivity, and augmenting human capabilities not necessarily replacing them… yet.”

Simply put, the agentic AI bandwagon is already full. Consider some recent headlines:

You could toss Amazon Q into the AI agent mix, but Amazon Web Services refers to it more of an assistant.

The catch is that the agentic AI we’re talking about today will need to improve dramatically to fully understand and make calls in the real world. You know the drill. First comes the buzzword and then the execution.

Speaking earlier this year at Google Cloud Next, Anthropic CEO Dario Amodei said: "One of my guesses is that if you want an agent to act in the world it requires the model to engage in a series of actions. You talk to a chat bot, it only answers and maybe there's a little follow-up. With agents you might need to take a bunch of actions, see what happens in the world or with a human and then take more actions. You need to do a long sequence of things and the error rate on each of the individual things has to be pretty low. There are probably thousands of actions that go into that. Models need to get more reliable because the individual steps need to have very low error rates. Part of that will come from scale. We need another generation or two of scale before the agents will really work."

Since those Anthropic comments, the company has developed its Claude family of large language models nicely.

Technology has never waited for a buzzword to work before talking about it nonstop. Rest assured, “agentic AI,” “AI agents” and the like will be discussed extensively going forward by enterprise software giants. Why?

AI agents are being pitched by enterprise software vendors because the entire category is going to be disrupted. Everything from the cross-selling of clouds, revenue models (seats to consumption and value) and platforms vs. product lines will need to be rethought. GenAI and AI agents are likely to become the primary user interface to software and that’s going to be a big headache for your go-to vendors.

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OpenAI releases o1-mini, a model optimized STEM reasoning, costs

OpenAI releases o1-mini, a model optimized STEM reasoning, costs

OpenAI released OpenAI o1-mini, a reasoning model designed to excel at Math and coding. OpenAI o1-mini highlights how models with focus is the next frontier.

The company also said o1-mini's cost is 80% cheaper than OpenAI 01-preview. ChatGPT Plus, Team, Enterprise, and education users can use o1-mini as an alternative to o1-preview to save money.

OpenAI said it trained o1 models without broad knowledge and optimized for STEM reasoning.

In a high school AIME math competition, o1-mini at 70% is competitive with o1 at 74.4%, but with lower costs. Coding had comparison. In other words, enterprises will determine the accuracy needed and optimize costs. The new models from OpenAI deliver much better math performance than GPT-4o.

OpenAI also made the case that slower answers are better for STEM subjects. GPT-4o was fast, but incorrect and the o1 models were correct with slower speeds. The company noted:

"Due to its specialization on STEM reasoning capabilities, o1-mini’s factual knowledge on non-STEM topics such as dates, biographies, and trivia is comparable to small LLMs such as GPT-4o mini. We will improve these limitations in future versions, as well as experiment with extending the model to other modalities and specialties outside of STEM."

OpenAI outlined its views on how LLMs will reason going forward, but there appears to be a bit of a shift away from one-do-it-all model. Humans are also beginning to see models more like a toolkit.

The company concluded:

"o1 significantly advances the state-of-the-art in AI reasoning. We plan to release improved versions of this model as we continue iterating. We expect these new reasoning capabilities will improve our ability to align models to human values and principles. We believe o1 – and its successors – will unlock many new use cases for AI in science, coding, math, and related fields."

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Adobe earnings: Solid Q3, but Q4 outlook light

Adobe earnings: Solid Q3, but Q4 outlook light

Adobe reported better than expected third quarter earnings as its primary segments delivered double-digit growth from a year ago. However, the fourth quarter outlook was lower than expected.

The company reported third quarter earnings of $3.76 a share on revenue of $5.41 billion, up 11% from a year ago. Non-GAAP earnings were $4.65 a share.

Wall Street was looking for Adobe to report third quarter earnings of $4.54 a share on revenue of $5.37 billion.

As for the outlook, Adobe projected non-GAAP fourth quarter earnings of $4.63 a share to $4.68 a share on revenue of $5.5 billion to $5.55 billion. For the fourth quarter, Wall Street was looking for earnings of $4.67 per share on revenue of $5.6 billion.

In prepared remarks, Adobe CEO Shantanu Narayen said the product advanced launched in the last 18 months "are delighting a huge and growing universe of users and enterprises."

"Our vision revolves around Adobe's deep technology platforms across Creative Cloud, Document Cloud and Experience Cloud which, when integrated, provide significant differentiation and value," said Narayen, who said adoption of Adobe AI features such as Firefly and Acrobat AI Assistant are driving demand. Adobe has surpassed 12 billion Firefly-powered generations across the company's platform.

Speaking on a conference call, Narayen said the fourth quarter is shaping up to be strong. "We saw the typical strength that we would see going into Q4. You're looking at the sequential guide. We're looking at it and saying it's the strongest ever Q4 target that we have put out there for Q4. I think we just continue to focus," said Narayen.

David Wadhwani, President, Digital Media Business at Adobe, added:

"Q3 was a little stronger than you expected, and for a good reason given seasonality. I think a lot of that can be explained by a few deals that would have historically just closed in Q4, closing earlier than expected in Q3, and that changed the dynamic in terms of the linearity that you would typically see between Q3 and Q4."

Wadhwani said Creative Cloud is seeing revenue gains from AI. "We have higher-value, higher-priced offers, thanks to AI innovation that's happening in the base plans that are impacting how the Creative Cloud business is doing," he said. "We also have a broader set of offerings than we've ever had now with web and mobile, including Premium and lower-priced offerings that are driving more proliferation."

By the numbers:

  • Digital Media revenue in the third quarter was $4 billion, up 11% from a year ago. Within that segment, Document Cloud revenue was $807 million, up 18% from a year ago and Creative revenue was $3.19 billion, up 10%.
  • Digital Experience revenue was $1.35 billion, up 10% from a year ago. Digital Experience subscription revenue as $1.23 billion, up 12%.
  • AI interactions within Adobe Acrobat was up 70% in the third quarter compared to the second quarter.

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Salesforce debuts Agentforce: Will enterprises pay $2 per AI agent conversation?

Salesforce debuts Agentforce: Will enterprises pay $2 per AI agent conversation?

Salesforce is rolling out AI agents via its Agentforce platform across its core clouds including Sales, Service, Marketing and Commerce. What remains to be seen is whether enterprises will pay $2 per conversation for Agentforce assuming no volume discounts.

The news drop from Salesforce wasn't that surprising given that CEO Marc Benioff has been talking about Agentforce and agentic AI since the company's second quarter earnings call. In addition, Salesforce has had a steady drumbeat of agentic AI themes leading up to Dreamforce. Benioff even previously mused about the $2 per Agentforce conversation model

Salesforce's biggest issue with Agentforce is that the AI agent bandwagon has rapidly filled up. ServiceNow's Xanadu release this week included AI agents and Google Cloud CEO Thomas Kurian also talked monetization for agentic AI. Oracle at CloudWorld also had some AI agent mojo.

Dreamforce 2024 is really about showing what Agentforce can do and move the conversation up the stack away from generative AI copilots to digital agents that are autonomous and can act on your behalf. Much of the technology behind Agentforce was acquired in last year's Airkit.ai purchaseSalesforce's acquisition of Own highlights small ball approach to M&A

Salesforce is also trying to thread the needle between blending humans and AI focusing on core strengths. In this AI agent vision applied to sales, humans focus on relationship building, industry knowledge, collaboration and goal setting while agents scale by answering questions, booking meetings, researching and collecting information.

Key items to know about Agentforce:

  • Data Cloud sits at the center of Agentforce as well as every Salesforce app. Data Cloud puts together all of the customer data as well as metadata.
  • Salesforce's Atlas Reasoning Engine is the brain behind Agentforce. Atlas is built on proprietary code that's designed to simulate how humans think and plan. The system evaluates user queries, refines them, retrieves data and then makes a plan to execute. Plans are then refined.
  • Agentforce has native integration with MuleSoft, Salesforce Flow and Apex.
  • Einstein Copilot has been upgraded as an agent under the Agentforce banner.
  • Agentforce will include Agent Builder to customize out-of-the-box agents, Model Builder and Prompt Builder.
  • Agentforce partners include AWS, Box, Coupa, Google, IBM, Workday, Zoom and others. This partner network has built more than 20 agents and agent actions available via Salesforce AppExchange.
  • Agentforce for Service and Sales will be generally available Oct. 25 with some components of the Atlas Reasoning Engine launching in February.

The upshot here is that Salesforce's clouds are now unified one core platform with Revenue and Orders Cloud, Marketing, Commerce and Tableau all on the same underpinning as Sales, Service, Platform and Industries. Data Cloud is the common thread.

Constellation Research analyst Holger Mueller said that the real story is the infrastructure behind the agents. 

"While the front end aspects of agent announcements are taking all the limelight it's the behind-the-scenes architecture innovation that is critical. This infrastructure is the difference in changing the future of work for people. And Salesforce has laid the foundation with its Data Cloud and now it's Atlas reasoning engine, combined with low code/no code across the key agent platform. Being able to compose performing agent applications through conversations is key to increase developer velocity and productivity." 

Ahead of Dreamforce, Salesforce highlighted a pair of Einstein Sales Agents including SDR (sales development representative) and a Sales Coach to enhance sales rep results. The company noted that agents are more impactful than bots because they are dynamic, outcome oriented and can adapt to various situations.

For Salesforce, Agentforce is the connective tissue that'll make the company's various clouds a cohesive platform.

Salesforce is going to back up Agentforce with an ongoing cadence of Data Cloud apps, Sales AI copilots and tools to accelerate value.

Here's a look at Salesforce's Agentforce lineup beyond SDR and Sales Coach:

  • Service Agent will replace chatbots with AI without preprogrammed scenarios.
  • Merchant aims to assist ecommerce merchandisers with promotions, site setup, goal setting, product descriptions and insights.
  • Buyer will help buyers find products, purchase and track orders via chat or portals.
  • Personal Shopper acts as a concierge on ecommerce sites.
  • Campaign Optimizer automates, analyzes, generates and optimizes marketing campaigns.
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Ford Pro aims to be software business focused on TCO

Ford Pro aims to be software business focused on TCO

Ford CFO Navin Kumar sounds like an enterprise software executive when he talks about Ford Pro, a unit focused on vehicles for businesses, and total cost of ownership, data and subscriptions.

Speaking at Goldman Sachs Communacopia + Technology Conference, Kumar noted the flywheel of data, vehicles, telematics, uptime and customer experience. Ford Pro includes commercial vehicles, all-electric trucks and vans and various services including telematics, telematics with dashcam, data services and fleet management.

The Ford Pro strategy is similar to Rivian's model: Build a fleet, create a data flywheel and deliver a great customer experience. See: How Rivian Data, AI, and a Software-Defined-Vehicle Strategy Is Paying Off

Kumar noted that Ford Pro has 600,000 paid software subscriptions and 32 dedicated elite service centers with 100 operational by 2026. Mobile repair orders grew 100% from a year ago in the second quarter. In the second quarter, Ford Pro delivered EBIT of $2.6 billion on revenue of $17 billion, up 9% from a year ago. Demand was driven by Super Duty trucks and Transit commercial vans. Demand for those vehicles outpaced production.

Kumar said:

"We're building out a fast, reliable, data driven service network that keeps vehicles on the road. And for Pro, this is a virtuous cycle. The more software subscriptions we have, the more data intelligence and analytics that flows into how our customers can operate their fleets more efficiently, how we can service these fleets more effectively and also make the software better and better.

So, for Pro, growing our software across all customer channels and use cases really builds out an intelligence mode that sustains our market leadership and helps our customers improve their bottom line."

Kumar said Ford Pro is looking to integrate hardware, software and cloud applications to improve customer productivity and uptime. "Our service is getting smarter and much more proactive to minimize vehicle downtime. For our customers, that's improving their bottom line. And for Pro, it is diversifying and growing our business into higher margin software and services which are more durable earnings streams," said Kumar.

Related: General Motors needs to fix its software issues quickly

Ford Pro is expanding into fleet management for small and medium sized businesses with a focus on driver management, inventory management, service scheduling and parts expense management.

Kumar said the telematics dashboard blended ARPU is about $20 per month and can vary based on size of fleet and use cases. Data services are priced lower. Rental companies want a full data pipe and the pricing starts at $5 a month and expands. On a blended basis, Ford Pro is seeing ARPU between $7 to $8 a month.

Kumar said:

"We run our software team like a software business. You have annual recurring targets, you have gross margin targets, you have churn targets. But from an enterprise standpoint, we want as many vehicles connected and need vehicles in our ecosystem that could drive differentiation and uptime and productivity. That has dividends when it comes to vehicle loyalty and market share leadership and growing our service parts business. From an enterprise holistic mix standpoint, it's about subscription growth."

Ford Motor is using Google Cloud's deep learning services to build simulations for virtual wind tunnels to replace computational fluid dynamics. Ford also leverages Google Cloud's database services

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Zoho Analytics revamp aims to connect, BI, data scientists, business users

Zoho Analytics revamp aims to connect, BI, data scientists, business users

Zoho launched a new version of Zoho Analytics that includes more than 100 enhancements in a bid to appeal to data scientists who can then feed business users easy to consume insights and models.

The company added multiple artificial intelligence (AI) and machine learning (ML) features to Zoho Analytics including an ML model-building studio, integration with OpenAI, and more than 25 connectors to third party business intelligence systems.

With the launch of Zoho Analytics 6.0, Zoho is looking to converge AI and ML in the context of business intelligence (BI) workflows with Zoho Flow integration. The bet is that Zoho and its pricing model can bring "AI-powered self-service BI" to multiple enterprise personas.

Historically, data science has been too complicated for broad business user adoption. Zoho Analytics is looking to bridge that data scientist/business user gap with a new DSML Studio for data science and machine learning and be one pane of BI glass via integration with Salesforce Tableau, Microsoft's PowerBI and other third-party platforms.

The new version of Zoho Analytics touches on many of the themes that Constellation Research analyst Doug Henschen has been highlighting including the combination of BI and generative AI, value plays in BI, and the importance of embedded analytics. “Zoho Analytics’ greatest strength is the value that it offers for very little money,” said Henschen. “The latest upgrade adds yet more features, particularly augmented analytics and data science capabilities, to bring more value to an already competitive platform.”

In a blog post, Henschen added:

"Zoho is not just a cost-competitive disruptor in the CRM, personal productivity and collaboration spaces; since 2009 the company also has been steadily gaining market share in the business intelligence (BI) and analytics arena."

According to Raju Vegesna, Chief Evangelist for Zoho, Zoho Analytics, which launched as Zoho Reports in 2009, is the first offering that integrates the company's investments over the last decade. Those investments include automation, no-code and low-code development, third party integration, machine learning and Zoho's Zia AI engine.

Zoho Analytics is part of Zoho Enterprise but can be purchased as a standalone application. Zoho Analytics has more than 17,000 standalone users up from 10,000 in 2020. Via the Zoho One suite, Zoho Analytics has more than 70,000 businesses that tap into the platform daily.

"The latest version of Zoho Analytics is one of the first solutions from the company that takes advantage of every one of these decades-long investments," said Vegesna. "The result is a democratized platform that is powerful, intelligent, and flexible enough to benefit everyone and anyone."

Zoho Analytics has four plans, the most popular plan is Premium at $115 a month billed annually for 15 users and 5 million rows. Zoho Analytics Enterprise is $455 a month billed annually for 50 users and 50 million rows. Additional users are $6.40 per user per month billed annually. Viewers are $80 for 25 viewers per month billed annually.

“The buying option that makes sense for organizations with 100 or more employees is Zoho Analytics Enterprise, which bundles everything, including Zoho Data Prep, Zia Insights, Ask Zia, Auto Analysis, DSML Studio, the analytic portal, and higher-level allowances for data connectors, storage, data refreshes, alerts, scheduled report delivery, and more,” said Henschen.

Here's a look at Zoho Analytics by category.

Data Management Hub

Zoho Analytics gets expanded data management tools including Stream Analytics, ETL data pipelines, metric enhancements and a bevy of connectors.

According to Zoho, Zoho Analytics now has more than 500 data connectors by adding 25 new connectors including streaming source options Google Cloud Pub/Sub, Kafka and the PubNub platform.

Zoho also made Zoho Analytics more accessible by giving business users the ability to create and manage ETL data pipelines, visual builder tools to build custom transforms and ML models with Python Code Studio. Zoho Analytics is also infused with Zoho's natural language with Ask Zia.

Zoho Flow, the vendor’s optional workflow engine, also is integrated with Zoho Analytics to orchestrate data pipelines. In addition, Zoho Analytics gains a new Metrics Layer to manage all business metrics in one place. Data apps can also consume the same metrics as Zoho Analytics Headless BI mode.

Generative AI

Throughout Zoho Analytics, Zoho has added generative AI capabilities. The platform features Open AI integration with retrieval-augmented generation (RAG) using Open AI APIs and bring your own keys. Users can more easily find public datasets and create formula and SQL queries.

Other genAI additions to Zoho Analytics include:

  • Zia Insights, Zoho's automated insights engine, now provides diagnostic analytics contextually.
  • Ask Zia, Zoho's natural language query AI copilot, now allows users to trigger actions and build custom data models. The Ask Zia Bot can also be integrated with instant messaging platforms including Microsoft Teams.
  • Auto Analysis, a tool within Zoho Analytics, has been enhanced to take advantage of the Metrics Layer and automatically generate metrics, reports and dashboards.

Data Science and Machine Learning Studio

Zoho added the Data Science and Machine Learning (DSML) Studio to Zoho Analytics. DSML Studio enables users to build custom machine learning models for business use cases.

DSML Studio includes:

  • AutoML, a no-code assistant to build custom ML models, to train, test, compare and deploy models.
  • Code Studio, a new Python code environment to create custom ML models. Code Studio can import Python models and external built libraries.

Extensibility

Zoho Analytics has a no-code builder for data connectors, actions, BI fabric and software developer kits.

Here's a look at other extensibility features:

  • BI fabric gives Zoho Analytics to consolidate insights from multiple BI platforms including Power BI and Tableau into one portal.
  • Zoho Analytics users can trigger actionable workflows and integrates with Zoho Flow, which has more than 500 app triggers.
  • No-code data connector builder to bring data from custom applications. Data connectors can be sold on Zoho Marketplace.

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Zoho Advances Its Value-Leading Analytics and Business Intelligence Platform

Zoho Advances Its Value-Leading Analytics and Business Intelligence Platform

Zoho Analytics 6.0 brings AI-infused upgrades to data management, natural-language interaction, and data science capabilities – all at superow prices. 

Zoho is not just a cost-competitive disrupter in the CRM, personal productivity, and collaboration spaces; since 2009 the company also has been steadily gaining market share in the business intelligence (BI) and analytics arena. Zoho Analytics 6.0, the latest upgrade of the vendor’s BI and analytics platform, announced on September 12, ups the ante by adding advanced, artificial intelligence (AI)-powered capabilities for data management, natural-language (NL) interaction, and data science. Although some of the tools are aimed at data professionals, they’re integrated with a platform that brings the power of insight, prediction and action back to ordinary business users.

There’s no doubt that competitive pricing has a lot to do with Zoho Analytics’ adoption by more than 17,000 organizations and three million users. What buyer would not at least consider a BI and analytics platform with all-inclusive pricing that comes in at less than $10 per user, per month (based on the annual pricing of Zoho Analytics Enterprise)? That does not mean that customers must sacrifice much when it comes to functionality. Zoho stays competitive with state-of-the-industry features, as plified by the three Zoho Analytics 6.0 upgrade themes detailed below.

Going Deeper on Data Integration and Data Management   

To recap some of the basics of Zoho Analytics, the platform is most often purchased as a multitenant software-as-a-service (SaaS) offering that runs on Zoho Cloud, which operates 16 data centers around the globe, with redundant data centers in North America, Europe, India, China, Japan, Saudi Arabia, and Australia. Zoho Cloud has stringent, transparent privacy policies and meets compliance requirements in multiple countries and jurisdictions (including the California Consumer Privacy Act in the U.S. and the General Data Protection Regulation in Europe).

Zoho Analytics is also available as a server-based offering deployable through the Amazon Web Services (AWS) and Microsoft Azure marketplaces or by customers themselves on other public clouds or on private clouds.

Where data integration and data management are concerned, Zoho Analytics offers out-of-the-box connections with more than 500 data sources, including cloud and on-premises databases, popular productivity tools and business applications, files, feeds, and spreadsheets. Zoho DataPrep, included with Zoho Analytics Enterprise, supports automated data modeling and blending, smart (augmented) data cleansing, no-code data transformation, data enrichment, and data cataloging.

Zoho Analytics 6.0 upgrades include new data modeling capabilities and a metrics store, above, that helps ensure consistency and promote reuse of approved metrics and measures.

Zoho Analytics 6.0 enhances the platform’s data integration and data management capabilities by offering the following:

  • New data connectors, including streaming options.  The pace of business is always accelerating, so Zoho has added pre-built connectors for popular streaming sources Google Cloud Pub/Sub, Kafka and the PubNub platform for real-time applications. Among the 25 other new connectors added with version 6.0 are app integrations with Oracle NetSuite, Expensify, and Monday.com, and data source integrations with Databricks, Google Cloud Storage, Neo4J, and Yellowbrick.
  • Ask Zia NL assistance within Zoho DataPrep.  In the 6.0 release, Ask Zia, Zoho’s NL copilot, has been added to Zoho DataPrep. Users can now simply ask it to “remove duplicates” or “join two datasets,” for example, to clean up or enrich data.
  • New metrics layer. Semantic modeling capabilities help to ensure data consistency, reliability, and reusability, so Zoho is stepping up on this front in Zoho Analytics 6.0 by adding data modeling capabilities, a metrics store, and deeper access control capabilities. The upgrade will make it easier to provide and secure consistent data and to standardize and reuse key performance measures.
  • Zoho Flow integration. The vendor has integrated Zoho Data Prep with Zoho Flow, the vendor’s lightweight workflow engine, providing an (extra-cost) option to meet more sophisticated data pipelining and data orchestration requirements.

Infusing AI Across the Platform

Generative AI (GenAI) continues to grab lots of attention, but it’s not the only form of AI that’s driving innovation. Zoho is infusing a variety of AI capabilities into Zoho Analytics to speed analysis and derive deeper insights:

  • Zia Insights gets diagnostic. Zia Insights is an existing AI/machine learning (ML)-powered automated insights feature that helps users spot variances, outliers, and trends; do comparative analysis; and get top insights through NL explanations. In the 6.0 release, Zia Insights gains diagnostic capabilities for root-cause analysis. This helps to answer the “why” questions, explaining with short NL narratives the key drivers behind changes in any measure or key performance indicator (KPI).
  • Ask Zia adds actions, languages and integrations. As of the 6.0 release, Ask Zia can handle complex calculations and trigger actions. For example, you can Ask Zia to create a new calculated field, generate a new report containing that field, and then send a PDF copy of the resulting report to specific users or groups. Ask Zia is also now multilingual, understanding and generating French and Spanish as well as English. Finally, the Ask Zia Bot can now be integrated with collaboration/messaging platforms such as Microsoft Teams, bringing NL analysis capabilities outside of the context of reports and dashboards.
  • Auto Analysis generates high-value reports and dashboards. Now that Zoho Analytics has a metrics layer, the platform’s augmented Auto Analysis feature has been enhanced to automatically generate metrics, reports and dashboards. With the click of a button, Auto Analysis can generate dashboards focusing on, for example, sales analysis, net revenue analysis, ad spend, or sales versus net spend. In case the results don’t quite fit the needs of the organization, customization features are available to tweak the automated output.
  • Open AI integration. Zoho Analytics’ bring-your-own-key (BYOK) integration with Open AI has been enhanced to provide contextual assistance for SQL query creation, metrics generation, and data-enrichment using public datasets. The integration also now supports retrieval augmented generation (RAG) against customer data without data sharing. To ensure security and privacy, only underlying metadata is shared with OpenAI.

Supporting Data Science and Machine Learning

Many organizations want to go beyond descriptive and diagnostic analytics – rearview analysis of what happened and why. They want to graduate to predictive and prescriptive analytics – gaining insight into what will happen and what should be done about it. Following this interest, many BI and analytics vendors are moving into the predictive domain.  

in the 6.0 release, Zoho is adding a new DSML Studio supporting-- you guessed it--data science and machine learning. DSML Studio is aimed at data scientists, data engineers and savvy data analysts, but once their data transformation and modeling work is done, the resulting predictive results can be shared with the broad base of ordinary business users through reports, dashboards, key metrics and so on. Salespeople, for example, could be exposed to leads predicted to be most likely to convert, and service agents could see if customers they are busy supporting are likely to churn.

Zoho Analytics’ new DSML Studio and its AutoML feature help customers go beyond descriptive and diagnostic analytics and move into the predictive realm.

  • AutoML.  DSML Studio’s AutoML feature draws from an assortment of pre-built algorithms – XGBoost, decision tree, random forest, adaptive boost, linear regression and so on – and automates feature selection, model selection, and hyperparameter tuning based on the selected data and type of prediction desired. The feature also supports testing, deployment, and management of resulting models.
  • Code Studio. Aimed more squarely at data scientists, DSML Studio’s Code Studio component is an integrated Python environment for custom model development.

Constellation’s Analysis

There’s more to the Zoho Analytics 6.0 upgrade, including analytic portal integration with Tableau and Power BI, but the overarching theme is adding more features, more AI/ML/GenAI capabilities, and more value to an already competitive platform.

As I detailed in my in-depth analysis of Zoho Analytics, among Zoho Analytics’ few weaknesses are the fact that it’s available as a service only on Zoho Cloud. That’s not a concern for customers using other Zoho apps that also run on Zoho Cloud, but customers with data concentrated on AWS, Azure, or Google Cloud have a choice: either live with cloud data connections (and their potential latency) or self-manage Zoho Analytics on a third-party cloud. One other drawback: Zoho Analytics is a view-only system lacking write-back capabilities, a drawback in certain embedded scenarios where interactivity with parent applications is desirable.

Again, Zoho Analytics’ greatest strength is the value that it offers for very little money.  There are entry-level price points, but the buying option that makes sense for any organization with more than 100 employees is Zoho Analytics Enterprise, which starts at $455 per month for 50 users, based on an annual subscription. Best of all, the Enterprise package includes everything, including Zoho Data Prep; Zia Insights; Ask Zia; Auto Analysis; DSML Studio; the analytic portal; and higher-level allowances for data connectors, storage, data refreshes, alerts, scheduled report delivery, and more.  

One last point I’ll make is about the Zoho Analytics support experience, which is “fantastic,” according to customer Kris James of Sparex. That’s not something I’m used to hearing from a lot of BI and analytics customers.

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