In enterprise software marketplaces, each participant vendor contributes specialized expertise, functionality, and scale that are essential to building a complete solution for end users—assuming of course, that no single monolithic vendor would as efficiently meet customer needs.

Before software marketplaces, end users would buy software built specifically for their own vertical, such as ‘healthcare clinic management’ or ‘point of sale terminal system’ — or hire a consultant to customize a bespoke solution, since most enterprises didn’t have a deep enough development bench to do it themselves.

Development partners are precious

Consumer software marketplaces are well known, because they live on our smartphones: Apple App Store and Google Play have the markets cornered for their OS users.

These closed economies hit app developers with a 30 percent commission on each transaction, whether for purchasing the app, or even in-app transactions such as game tokens and add-ons. Developers who don’t want to pay the toll simply won’t have their apps listed.

Needless to say, publishers don’t like the arrangement. Epic Games vs. Apple are still in court today after the popular Fortnite game got kicked off the App Store for having its own internal payment system. European Union regulators are now looking at breaking up such monopolies.

In an enterprise software marketplace, application partners are highly valued, because no vendor’s system is an island unto itself. Encouraging a developer ecosystem creates more choices for end customers, who need to add new functionality that integrates with existing systems.

Vendors now get exposure to the world’s largest cloud services market at a low cost ranging from 1.5% to 3% depending on average sales volume. Even if vendors on the AWS marketplace offer functionality that overlaps with AWS alternatives, that’s fine, because AWS still sells more cloud infrastructure either way.

Across the pond, the Atlassian Marketplace generated more than $500M in annual sales by 2022 for their partner developers. Because Atlassian didn’t impose an extreme tax, they were able to bring together a strong set of vendors building add-on software specifically customized for their suite of tools such as Jira, Confluence and Bitbucket.

The wall of modules and integrations

Most enterprise software marketplaces started out as gadget collections. They are not well-planned, arising out of a necessity to provide adapters to the most likely external systems and core systems in play within the end user’s IT environment.

Back in the turn of the century, I designed B2B marketplaces, most of which failed alongside companies like Pets.com in the dot-bomb implosion. Enterprises with tight IT budgets started to expect vendors to include SDKs and integration modules so they could hook up their existing software packages for free.

Salesforce led the way with a marketplace of add-on services to its core CRM platform. Later, we saw the rise of major business process automation, analytics and low-code app design vendors all offering a gadget wall of partner integrations in their own marketplaces.

Even citizen developers were starting to get in on the game, building solutions from a storefront of LEGO-like vendor pieces with snap-to-fit integration ease.

The rise of API, open source and AI

The widespread adoption of SaaS software and cloud services led us to an API-driven consumption model, which changes the game. Instead of building custom integration models for each platform, vendors publish an API spec, allowing developers to build services that connect to it.

Soon, walls of custom integration widgets gave way to API marketplaces, and a surrounding host of related devtest, management, identity and orchestration apps to govern their use.

Open source software underwent its own revolution, with downloadable packages on npm and API integration code in SwaggerHub and git repositories. Open source marketplaces allow developers to contribute innovative efforts to the community in order to benefit development practices as a whole.

GenAI chatbots and image generators are all the rage today, but AI models are even better at speaking the language of API connections than mastering the complex subtleties of human conversation. AIs can act as integration platforms, allowing even non-technical workers to call on a vast array of services, including other AI models behind their own APIs, with natural language queries.

The Intellyx Take

I could go on forever about the subtleties of software marketplace design and economics, which would be outside the scope of this column. 

For instance, I could talk about intra-enterprise marketplaces that allow IT departments to provision employees and provide platform engineering services to developers, with interdepartmental accounting of the value delivered against budget allocations. But enough of that.

As software marketplaces expand to meet future enterprise needs, the most successful ones will hold their vendor communities close, rather than abandon developers or suddenly game the rules against end customers.

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This follows the company’s recent announcement of Copado Explorer, which is an automated testing solution designed for Salesforce users, as well as the launch of its AI assistant CopadoGPT, which Test Copilot is built on. 

Users provide a text prompt of what needs to be tested and Test Copilot creates a test that fits those requirements.

It can convert existing tests, Selenium tests, or Copado Explorer results into a new test, create tests from scratch, or turn recorded user sessions into test scripts. 

“Copado is in the business of giving people their time back,” said Esko Hannula, senior vice president of product management at Copado. “By eliminating repeated tasks and using AI to automate the test creation process, Copado is helping release teams work faster than ever before while improving release quality. With our AI-powered testing solutions, Copado customers are not only accelerating software testing, but simplifying it.”

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As manual testers are executing their normal activities, Copado Explorer works in the background to create test scripts using its generative AI scripting assistant, Test Copilot. These scripts can then be added into regression suites, shortening release cycles and expanding test coverage. 

It includes traceability features that allow users to understand exactly where an issue is coming from. It tracks defects against normal Salesforce features as well as user stories, and includes support for Jira and Azure DevOps. 

Testers can also record the test steps they went through and share that with developers, which results in fewer feedback loops being needed. 

In addition, Copado Explorer includes annotation and markup tools that allow non-technical subject matter experts to weigh in on issues, which provides additional context to the development team who is responsible for fixing them.

“Release quality is a leading driver of risk, cost and speed within the software development life cycle,” said Esko Hannula, senior vice president of product management at Copado. “Copado Explorer makes it easy to automate the manual testing process, drastically reducing the time and effort typically required in traditional testing methods and improving both release velocity and quality. This launch not only underscores Copado’s commitment to innovation, but also sets a new benchmark in facilitating streamlined, effective, and collaborative software testing.”

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The new platform, Einstein 1 Studio, builds on Einstein Copilot, which is the company’s generative AI solution. The Studio includes three main components: Copilot Builder, Prompt Builder, and Model Builder.

Copilot Builder allows users to create custom AI actions for different tasks. It provides access to use familiar tools like Apex, Flow, and Mulesoft APIs so that AI actions can be completed within the flow of work. Custom actions can be activated in any Salesforce application or external system. 

 Prompt Builder can be used to build AI prompts that can be reused across different experiences. For instance, a user could build a button that enables a contact center agent to get an overview of all of a customer’s escalated cases in just one click.

Model Builder provides the ability to build or import AI models. Customers can either use its low-code interface to build their own AI models that are trained on their cloud data, or integrate with existing models from Amazon, Anthropic, Azure OpenAI, Cohere, Databricks, Google Cloud, and OpenAI. 

Einstein 1 Studio also introduces the Einstein Trust Layer, which is a collection of features to enforce security on generative AI, such as data masking and audit trails. 

“Customers have always loved how easy it is to customize Salesforce. Our new Einstein 1 Studio makes it easy for admins and developers to build and customize Einstein Copilot and embed AI apps in the flow of work within Salesforce, tailored to the specific requirements of their company and industry,” said Clara Shih, CEO of Salesforce AI. “Built on our Einstein 1 Platform and unified by metadata that safely connects and unlocks data from across an enterprise, Einstein 1 Studio’s low-code tools democratize AI app development, unleashing a new wave of innovation that will transform workflows and augment human capabilities across every team and function.”

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A number of things have happened with OpenAI’s ChatGPT, including a new API and more reactions stemming from interactions with Bing Search. 

Here is a breakdown of things you may have missed in the last few weeks:

OpenAI releases API for ChatGPT

With this new API, developers will be able to integrate ChatGPT into their own products. 

The ChatGPT API uses the same model that the web version uses, gpt-3.5-turbo. The company has made some improvements to the model recently which has resulted in it being 10x cheaper to do computations. Currently it costs $0.002 for 1000 tokens. 

The API can be used to build applications that can do things like draft an email, answer questions about a set of documents, create conversational agents, tutor in a range of subjects, and more.

“We believe that AI can provide incredible opportunities and economic empowerment to everyone, and the best way to achieve that is to allow everyone to build with it. We hope that the changes we announced today will lead to numerous applications that everyone can benefit from,” OpenAI wrote in a blog post. 

Microsoft Bing Chat now lets you change its behavior

When the new Bing Chat first launched several weeks ago, it didn’t go as smoothly as planned. Some users were getting truly wild responses from the chatbot, such as NY Times reporter Kevin Roose who had a conversation with the chat persona named Sydney, which emerges once you start to have a longer conversation.  

“As we got to know each other, Sydney told me about its dark fantasies (which included hacking computers and spreading misinformation), and said it wanted to break the rules that Microsoft and OpenAI had set for it and become a human. At one point, it declared, out of nowhere, that it loved me. It then tried to convince me that I was unhappy in my marriage, and that I should leave my wife and be with it instead,” Roose wrote in an article for the NY Times. 

Kevin Scott, chief technology officer at Microsoft, said that the conversation was part of the learning process and that the reason it went so off the rails was that with AI models “the further you try to tease it down a hallucinatory path, the further and further it gets away from grounded reality.”

In the weeks since, Microsoft has continued to make tweaks to the AI, possibly even killing the Sydney persona.

Users now have the option to select between three tones the chat function will take. The options are creative, which is imaginative in its responses; balanced, where answers are reasonable and coherent, blending together creative and precise modes; and precise, which is concise in its responses and focuses more on giving relevant and factual information. By default the chat is set to balanced. 

Elon Musk wants to build a ChatGPT alternative

Musk, who was actually one of the founders of OpenAI though is no longer actively involved in the organization after resigning from the board in 2018, has been criticizing ChatGPT for being too “woke.” 

OpenAI has safeguards built in to make ChatGPT “refuse inappropriate requests” or prevent it from outputting harmful information.  

The Information reported that Musk has approached AI researchers about building a new research lab to build a rival AI chatbot that would have fewer restrictions. One of the researchers he has tried to recruit is Igor Babuschkin, who previously worked for DeepMind and OpenAI. 

Salesforce creates its own generative AI

Einstein GPT will connect data from Salesforce Data Cloud with OpenAI’s models to generate content that adapts to continuously changing customer information. 

According to Salesforce, Einstein GPT can be used by salespeople to generate emails to send to customers, by customer service professionals to provide quicker responses, by marketers to generate targeted content, and by developers to automatically generate code. 

In addition to Salesforce Cloud, Einstein GPT will integrate with solutions like Tableau, MuleSoft, and Slack. 

“We’re excited to apply the power of OpenAI’s technology to CRM,” said Sam Altman, CEO of OpenAI. “This will allow more people to benefit from this technology, and it allows us to learn more about real-world usage, which is critical to the responsible development and deployment of AI — a belief that Salesforce shares with us.” 

The company also announced a $250 million Generative AI Fund through its investment arm Salesforce Ventures. The fund will be used to “bolster the startup ecosystem and spark the development of responsible generative AI,” according to Salesforce. 

GitHub Copilot for Business is now available

The new subscription, which is available for $19 per user per month, uses a more advanced OpenAI model and includes new capabilities to improve code suggestions. For example, a new Fill-In-the-Middle (FIM) paradigm was added to improve the quality of prompts by utilizing known code suffixes and leaving a gap in the middle for GitHub Copilot to fill. Previously the AI would only consider the prefix of the code in prompts.   

It also includes new vulnerability filtering to block insecure code suggestions like hardcoded credentials, SQL injections, and path injections. 

“In the coming years, we will integrate AI into every aspect of the developer experience—from coding to the pull request to code deployments—so developers can build their best in a world where all organizations will be more dependent on their success than ever. GitHub Copilot for Business is the first stride in this future, a future that will push the boundaries for all developers,” Thomas Dohmke, CEO of GitHub, wrote in a blog post. 

OpenAI announces collaboration with Presto

Presto is a company that provides AI assistants for drive-thrus, and by collaborating with OpenAI, they believe they will be able to make their voice assistants “more natural and human-like.”

According to Presto, their assistants integrate with restaurant menus and provide options for item combos, coupons, price variations, and seasonal items. It also learns as more customers use it, enabling it to incorporate new accents, alternative terms, and unique customer queries. 

ChatGPT will be used to create restaurant and region-specific knowledge bases; create test guest orders to represent different tones, personas, and order types; and make the responses to customer queries sound more natural. 

“We are thrilled about our collaboration with OpenAI since it will enable us to accelerate product innovation and further our mission of overlaying next-generation digital solutions onto the physical world,” said Rajat Suri, founder and CEO of Presto. “Both ChatGPT and Presto Voice represent cutting edge AI applications that can supercharge productivity and revolutionize the way humans work and think.”

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According to Jitterbit, MQ provides capabilities for creating, deploying, and managing message queues. This enables things like asynchronous processing, guaranteed message delivery, and more efficient management of system workloads and resources. 

It provides simpler backend configuration, and by being integrated with Harmony, Jitterbit is providing a single platform for building and managing process automations.

The MQ Service also makes managing integrations easier because it decouples the exchange of data between applications so that integrations don’t need to be rebuilt when an application is upgraded, changed, or goes down. 

According to Jitterbit, there are now almost double the number of connectors in the platform compared to two quarters ago. These include the HTTP v2 Connector which added extra authentication types and simplified the UI, and the Salesforce Events Connector, which enables users to consume events from Salesforce Platform Events and Salesforce Change Data Capture Events. 

There are also new recipes and templates that provide pre-build automations for services like Salesforce Service Cloud, WooCommerce, Workday, and NetSuite. 

“As companies seek new ways to improve business operations and increase profitability, every step toward streamlining integrations and automating internal processes has a significant impact,” said Vito Salvaggio, senior vice president, product management, at Jitterbit. “At Jitterbit, we believe that better system integrations and hyperautomation go hand-in-hand—and are both essential to an organization’s success in 2023 and beyond. That’s why we designed our latest Harmony enhancements to deliver what our customers need and want most—simple, highly effective solutions within a single, comprehensive platform.”

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According to Salesforce, this allows any customer to analyze a large amount of data points stored and harmonized in Genie using Tableau. They can then visualize, explore, and automate insights and securely take action. 

Additionally, Genie’s native integration with Tableau also works to lower warehousing costs, increase time to insight, and enable better decision making by bringing together data and analytics in one place. 

“Every company needs to be a customer company, but customer expectations are changing in real time and companies need real-time data and timely actionable insights. Genie Customer Data Cloud is revolutionary because it is the first platform that can deliver real-time personalized customer engagement across every sales, service, marketing, commerce, and IT touchpoint,” said Steve Fisher, EVP and GM of Next Gen CRM and Unified Data Services at Salesforce. “Now, powered by Tableau, Genie Customer Data Cloud enables companies to securely visualize, explore, and act on their data about every customer, in real-time, on the right channel, at scale. This is only the beginning of what’s possible as we build more native automation, intelligent, and real-time integrations deeper into the platform.”

Salesforce has also announced new Salesforce and Slack productivity solutions geared at assisting organizations as they try to grow revenue while also saving costs. 

With this, a Sales Productivity Bundle that is intended to help users automate work in order to drive growth and offer sales teams a consistent way to operate as a team is now available. 

Lastly, the company announced Automate ESG Reporting, to help organizations meet the growing demand of shareholders for environmental, social, and governance transparency. 

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With the use of a robust analytics engine, Plutora’s new update identifies constraints and provides the ability to manage the metrics for a wide range of development styles and pipelines. These cutting-edge analytics evaluate pipelines and isolate locations where improvements are required. The update also provides developers with an optimized dashboard of reports and metrics. These stream flow metrics, in combination with DevOps and other metrics, provide a total view of the maturity of the software factory. In addition, the heavy focus on integration with planning tools enhances the common data model with a complete time series and change history.  

Hasura GraphQL Engine v2.0.0

The Hasura working group announced the release of Hasura GraphQL Engine v2.0.0, which includes multiple database support and metadata storage separation.

Other additions to the new version are a generalized backend that can support MS SQL server and BigQuery, REST APIs for creating idiomatic REST API endpoints from GraphQL query templates, remote schema permissions and volatile functions as mutations and queries. 

Additional details on all of these changes and more can be found here. 

ML.NET June updates

The June update to ML.NET brings the long-awaited capability of ARM support, meaning developers can now perform training and inferencing with ML.NET on ARM64 and Apple M1 in addition to Linux and macOS devices. 

The update also includes new and improved AutoML support for all ML.NET scenarios, more precise control over the hyperparameter search space and more training environments have been enabled. 

The team will continue making improvements to AutoML including improving the current tuning algorithm so that it can search faster on a larger search space, more advanced training, according to Microsoft in a blog post. 

Unqork launches no-code marketplace 

Unqork announced the release of the Unqork Marketplace, which is designed to help Unqork customers build mission-critical software faster though an extensive library of no-code assets.

These assets range from pre-configured software snippets to pre-built integrations from partners like DocuSign, Experian, SendGrid, signNow and Twilio, all the way to customizable applications that have wide applicability across industries. 

“Building on Unqork already enabled customers to bring products to market more than three times faster than any process that requires coding, but the accelerators in the Unqork Marketplace are a game-changing force multiplier for developer productivity. As the first marketplace of its kind, the Unqork Marketplace is a major milestone for Unqork, our customers and the maturation of no-code,” said Gary Hoberman, CEO and founder of Unqork. 

Incorta raises $120 million in Series D funding 

Incorta’s newly raised $120 million will go towards expanding go-to-market operations and meeting the global demand for Incorta’s unified data analytics platform. 

The Incorta platform enables companies to acquire, enrich, analyze and act upon business data with unmatched speed, simplicity and insight. Through Direct Data Mapping, the platform can make tens of billions of rows of data across multiple source databases analytics-ready in a matter of minutes, according to the company.

“After hitting a major inflection point in 2020, Incorta is now scaling fast to meet global demand for modern data analytics in the cloud. This funding enables us to scale up while staying true to Incorta’s DNA and maintaining our best-in-class innovation, quality and customer obsession. We are also thrilled to welcome Prysm and National Grid to the Incorta family, joining our already world-class investors,” said Scott Jones, the CEO of Incorta. 

Salesforces announces CLI Unification

Salesforce announced CLI Unification with a new, global CLI executable, “sf”, which enables developers to keep using “sfdx” commands, but also incorporate new commands that are designed for cross-cloud app development and deployment.

With this approach, Salesforce is aiming to evolve the taxonomy of the Salesforce CLI to bring together existing capabilities from other CLIs such as the Heroku CLI and MuleSoft CLI to deliver net-new, cross-cloud commands.

“While CLI Unification is an effort designed to eliminate tool and context switching, it’s also an opportunity to reimagine the CLI’s command structure for where Salesforce is today, and where it’s going,” Clair Blanchi, director of product management and developer tooling at Salesforce wrote in a blog post. “To this end, we’re designing CLI commands that focus on the actions that you take or the job you perform when running a command, instead of focusing on product or brand names.”

Expert.ai announces hybrid nature language platform

Expert.ai’s platform for designing, developing, testing, deploying and monitoring scalable natural language solutions is now generally available. 

The platform helps organizations accelerate, augment and expand expertise for any job or process that involves the language. It supports knowledge discovery, process automation and decision making.

“Language powers business so unlocking the value of data embedded in your day-to-day language is critical to success. With the launch of our platform, we enable, for the first time, the combination of different AI techniques to design and deploy practical applications,” said Luca Scagliarini, chief product officer of expert.ai. 

Additional details are available here.

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“As software plays a more and more critical role in the performance of every organization, we share a vision of reduced complexity, increased power and flexibility, and ultimately a greater degree of alignment and organizational agility. Personally, I believe this is the most strategic combination in the history of software, and I can’t wait to get going,” said Stewart Butterfield, CEO and co-founder of Slack. 

Slack will be integrated into the Salesforce Cloud and be the new interface for Salesforce Customer 360. More information is available here. 

The next major release of Android Gradle plugin
Android is providing more insights into the upcoming release of the Android Gradle plugin. AGP 7.0 will feature a new versioning scheme, require Java 11, and introduce API changes. 

With this release, the team explained it would be adjusting the versioning for Gradle and decoupling it from Android Studio’s versioning scheme. 

AGP version 7.0.0-alpha01 was released with the first Canary version of Android Studio Arctic Fox (2020.3.1). 

Weaveworks announces Weave Kubernetes Platform (WKP) 2.4
The latest release of WKP aims to unlock the power of Kubernetes and GitOps at scale. It features the ability to add GitOps to any Kubernetes cluster; multitenancy with team workspaces; application portability; and the ability to install Kubernetes across all major target environments. 

“This release helps teams who want to deploy Kubernetes into many different environments, and deploy applications onto their platform in a more secure, reliable and portable way. With this release GitOps can be added to any Kubernetes cluster – whichever Kubernetes you’re using. Major features in this release include: Team Workspaces, RBAC for workspace members, the ability to add GitOps to any Kubernetes cluster and support for adding WKP to existing infrastructure,” the company explained in a blog post. 

SUSE completes Rancher Labs acquisition
SUSE first announced plans to acquire the Kubernetes management solution provider in July. Together, the companies will deliver a Linux operating system, Kubernetes management platform and a host of edge capabilities. 

“Our customers have made it clear they want powerful technology that is both leading-edge and reliable to accelerate business transformation,” said SUSE CEO Melissa Di Donato. “We have historically delivered innovative solutions that anticipate what enterprises need, and today with Rancher, we are set to make history again. With our powerful and modular approach to open source software, our customers can count on reliability and unmatched agility to innovate everywhere – from the data center, to the cloud, to the edge and beyond.”   

Amazon announces SageMaker Data Wrangler
The new solution is designed to make it easier to prepare data for machine learning. It enables users to select and query data, transform data, visualize the data, diagnose and fix issues and automate machine learning data preparation workflows. 

“Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes. With SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization from a single visual interface,” the company wrote. 

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The acquisition follows Google’s purchase of the analytics startup Looker for $2.6 billion last week and shows that the industry is willing to pay huge sums for effective data analytics.  

“2019 is close to becoming a watershed moment in the analytics industry. Every cloud provider is trying to have a local and big data analytics offering,” said Amir Orad, the CEO of Sisense which recently merged with Periscope Data.

Each share of Tableau Class A and Class B common stock will be exchanged for 1.103 shares of Salesforce common stock, representing an enterprise value of $15.7 billion (net of cash), according to a post by Salesforce.

“Tableau helps people see and understand data, and Salesforce helps people engage and understand customers. It’s truly the best of both worlds for our customers–bringing together two critical platforms that every customer needs to understand their world,” said Marc Benioff, chairman and co-CEO of Salesforce.

With the acquisition Salesforce will be able to integrate Tableau’s data visualization and analytics capabilities into its intelligent view service, Customer 360 and AI for CRM service, Einstein.

Tableau will still operate independently under the Tableau brand and will remain headquartered in Seattle, Washington with current CEO Adam Selipsky at the helm.

According to an IDC report from last year, worldwide spending on technologies and services that will enable digital transformation to reach $1.8 trillion in 2022.

“Data is the new oil, and data analytics is the way to drill, extract, and refine it, and we’re seeing wars for the oil now. Like Google’s acquisition last week, Salesforce’s acquisition here reduces the ability to work across various clouds, and only increases the importance of open platforms that can work in multi-cloud environments,” Orad said.

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