This approach enables organizations to adapt quickly to changes, making application and workflow automation deployment faster and easier. Additionally, Creatio Quantum introduces new components, generative AI, and a governance app, providing users with greater freedom in automation, the company explained.

With the introduction of Quantum, Creatio now fully embraces a composable approach, constructing all product functionality using pre-built components and blocks. At its most fundamental level, this consists of elements like widgets or sets of fields.

Creatio has disassembled all features of its CRM suite into components, blocks, and apps. This not only allows users to construct distinctive solutions using pre-made components and blocks but also enables them to utilize pre-built apps to meet their specific needs.

A highly sought-after feature, generative AI, has now been integrated into all of Creatio’s products, using models from OpenAI. According to Creatio, generative AI complements and expedites the no-code development process by automatically generating templates, components, or entire applications based on user-provided text input. This significantly reduces the time and effort required by no-code app creators to transform basic requirements into prototypes.

The launch of Quantum takes a further step in enabling businesses to adapt, create, and innovate with unparalleled efficiency, Creatio added.

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According to Salesforce, together the two companies will be able to help accelerate digital transformations for their customers. They will allow customers to create better user experiences and make smarter decisions more quickly.

“Every digital transformation starts and ends with the customer,” said Marc Benioff, chairman and CEO of Salesforce. “Together, Salesforce and MuleSoft will enable customers to connect all of the information throughout their enterprise across all public and private clouds and data sources—radically enhancing innovation. I am thrilled to welcome MuleSoft to the Salesforce Ohana.”

After the acquisition, MuleSoft will continue on with the company’s vision of application networks with its Anypoint Platform. In addition, MuleSoft will power the Salesforce Integration Cloud, enabling customers to drill down into data and create intelligent customer experiences.

The acquisition is expected to be completed by July 2018, as long as customary closing conditions are satisfactory.

“With the full power of Salesforce behind us, we have a tremendous opportunity to realize our vision of the application network even faster and at scale,” said Greg Schott, Chairman and CEO of MuleSoft. “Together, Salesforce and MuleSoft will accelerate our customers’ digital transformations enabling them to unlock their data across any application or endpoint.”

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According to stats from IDC, 80 percent of applications will have an AI component by 2020. To keep pace with these innovations and expectations, developers will need to create intelligent and personalized app experiences. With new platform services with Salesforce Einstein, a comprehensive AI for CRM, developers can create custom deep learning models to fit their business needs, and compete with other intelligent apps on the market.

One update to the portfolio includes Einstein Sentiment, developers can classify the tone of any text, from emails or social media posts, as a way to determine customer attitudes. For instance, developers can determine whether a statement like, “One hour wait on hold and I finally get some customer service.” It will recognize whether the statement is positive, negative, or neutral.

Customers can retrain these models to fit a particular niche industry, bringing examples to the sentiment model, branch that model off, and have their own sentiment model, according to Salesforce.

Einstein Intent is another platform service added, and this allows developers to train models to classify the intent of customer inquiries to automatically route leads, or personalize marketing campaigns. A customer could use Einstein Intent to build a custom application that automatically classifies inbound customer support queries to identify which customers are experiencing shipping problems. Then the company can provide support messaging and tracking details, according to Salesforce.

Einstein Object Detection is one other service added, and this lets developers train models to recognize multiple unique objects within a single image, as well as location, size, and quantities of those objects. For instance, a beverage company can streamline the inventory of soda in vending machines by automatically analyzing photos of the shelves to count the product, and then calculate a new product order.

In addition to these new platform services designed to create custom deep learning models for businesses, Salesforce’s interactive and gamified learning platform, Trailhead, now has new Trails from Atlassian, GitHub and Salesforce.

Trailhead takes developers on free, guided learning paths, and at the end of every “Trail,” they are given badges to display their knowledge and competency in developer skills. With this new update announced today, developers can receive new badges like Agile Basics and Agile Frameworks from Atlassian, or GitHub’s new Git and GitHub basics badge on Trailhead. Developers can also receive badges from Salesforce, like the Sales Cloud Platform badge or the Service Cloud Platform badge.

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Python Fire does not require developers to do any additional work, define arguments, set up information, or write a main function to define how the code is run. “It uses inspection to turn whatever Python object you give it—whether it’s a class, an object, a dictionary, a function, or even a whole module—into a command-line interface, complete with tab completion and documentation, and the CLI will stay up-to-date even as the code changes,” wrote David Bieber, software engineer for Google Brain, in a blog post.

Rust focuses of productivity
The Rust programming language team is laying out a major initiative it has for this year: To improve the ergonomics of the core language. According to the team, this will help improve productivity and reduce the learning curve.

“Ergonomics is a measure of the friction you experience when trying to get things done with a too,” wrote Rust developer Aaron Turon in a blog post. “You want to achieve a state of ‘flow,’ in which ideas and intuitions are steadily transformed into working code with a minimum of fuss. (And, with Rust, we want that code to be reliable and fast as well.)”

The team will be using the road map tracker to organize ergonomic improvement ideas, and will try to reimagine and evaluate how newcomers approach Rust.

Progress adds connectors to DataDirect Hybrid Data Pipeline
Progress has announced a suite of prebuilt data connectors as part of the DataDirect Hybrid Data Pipeline. The connectors are designed to provide open data connectivity to SaaS CRM solutions such as Microsoft Dynamics, Oracle Sales Cloud, Salesforce, SugarCRM and Veeva CRM.

“ISVs in the analytics and data-management space need a way to easily integrate with and pull data from a wide range of CRM solutions,” said Dion Picco, General Manager, data connectivity and integration at Progress. “Our support for SaaS CRM with open SQL and REST connectors provides ISVs with a great option to instantly connect standalone tools to CRM data for advanced analytics capabilities.”

Talend releases Apache Beam powered Big Data solution
Talend has announced it is using Apache Beam for self-service and Big Data preparation. Apache Beam is a unified programming model for batch and streaming data-processing pipelines. The new Data Preparation solution is designed to provide users the ability to access, cleanse and analyze large datasets.

The solution’s capabilities allow customers to access any data source and share it across users and groups; utilize a pre-configured data dictionary; and crowdsource new data definitions.

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Dubbed Einstein, these 17 new features can be used to build artificial intelligence on top of existing Salesforce datasets. Companies with existing Salesforce.com accounts and applications will be able to apply machine learning through it across their asset portfolios.

John Ball, general manager of Einstein, said that this is now a major new piece of the Salesforce product line. As such, Einstein will see three major releases per year. These AI services are available to all Salesforce customers, from Apex developers to Lightning users.

(Related: What does AI look like today?)

“Einstein can really transform the way everyone works,” said Ball. “We’ve all seen the consumer-world, AI-powered, smarter, more personalized applications. What if you have that same AI-powered smart personalized capabilities in Salesforce apps? Einstein is all about doing that.”

Ball said that Einstein is targeted at business users, not developers. “Historically businesses have not been able to apply AI to their business because it’s just really hard. Einstein changes that: It’s built right into the Salesforce platform,” he said.

Ball added that Salesforce takes “all this great data from millions of users every day, structured CRM information, but also e-mail, calendars, interaction data like web-clicks on ecommerce sites” and other sources. Then it applies “deep learning and machine learning to discover insights, predict outcomes, and since Einstein is built deeply into the platform, it lets us make predictions in the context of the business,” he said. Thus, salespeople using CRM can utilize Einstein to predict the probability of converting a lead.

Other updates
Mike Rosenbaum, executive vice president of CRM apps for Salesforce, introduced updates to the company’s Lightning Bolt framework. “It takes the Lightning experience and extends it to portals and community cloud, and gives partners the ability to give tailored experiences. Our customers can then easily deploy to their customers, with applications like a store operations portal,” he said.

Rosenbaum went on to state that there have also been “small changes to the UX that will have dramatically big improvements in productivity. We’re switching to a horizontal navigation bar with shortcuts into each category.”

Woodson Martin, general manager of Thunder and IoT Cloud at Salesforce, detailed the changes to this year-old platform for Internet of Things applications. He said that Thunder has added device profiles to its capabilities, which allows users to “visualize both the streaming event data with all the CRM data and other data from other systems, and be able to bring that all to bear into a single profile to make these intelligent decisions. This provides a platform for very rapid iteration and testing and improvement for these cycles.”

Elsewhere at Dreamforce, Salesforce unveiled new partnerships and API-based integrations. One of the most discussed partnerships at the show was with Quip, a business productivity and communications platform. Quip introduced deeper integrations to Salesforce, which allow users to pull live information into web-based Quip spreadsheets directly from Salesforce’s databases.

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Alex Dayon, Chief Product Officer at Salesforce, detailed the platform’s features, particularly those for commercial mobile development. Customers like Dunkin Donuts, GM and Intuit were shown as examples of successful Salesforce-based mobile applications.

(Related: How AI can help blind programmers)

Dayon also intimated that the future of the Salesforce platform will be heavily focused on AI. As proof, he cited Salesforce’s 2016 AI and machine learning acquisitions: MetaMind, Implisit and PredictionIO. It also purchased MinHash and Tempo AI, both machine learning companies, last year.

Parker Harris, cofounder of Salesforce, said that developers have a lot of complexity to deal with today, thanks to multiple platform options. “You’ve got apps on your phone, you have iPhones, Android phones, watches, laptops; it’s crazy,” he said. “If you’re a developer, you have all these different development environments. That’s why I delivered Lightning.

“Lightning is about building once and running everywhere. We talk about Lightning as an app, as an experience, but what I love is Lightning as a platform. Code is great, but my mission since I started Salesforce…is to figure out how we can have less code. How can we make things more and more declarative?”

Harris described the benefits of the Lightning platform, such as that developers can offer their applications for sale on the Lightning marketplace. Harris then detailed some forthcoming changes to the platform.

“Today, you have to write a controller that accesses the data,” he said. “Now we give you Lighting Data Services to handle that for you.” He added that Lightning will, this fall, add more core components, app branding options, inline edits, global navigation, components testing, and mass actions for developers.

Adam Seligman, executive vice president at Salesforce, said that the Force.com platform will also receive new capabilities and tools this year. That platform will get a new debugger, more enhancements for the Force.com platform within the Eclipse IDE, and a compiler with support for partial compilation.

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“Playing nice” with each other is something application users wish for as well. They want the cloud applications they use to just work together, nicely. They want their applications to share customer data, employee data and contact data with each other without having to call their IT departments . In today’s world, it’s often nasty business to share data across applications in the cloud, mapping fields and having technologies help each other versus hinder.  As application developers it becomes our responsibility to take this burden away from our customers, to deliver them apps that instantly cooperate with their other applications.

Enter the Next Generation of Application Integration: Building Cooperative Apps.
Cooperative Apps can instantly share data with other applications in the cloud, without placing an integration burden on the business or user who purchased the app. They work seamlessly with the other apps fitting within their solution space. Cooperative Apps “play nice” with other applications. They share data and seamlessly communicate with other applications just the way you want them to. Cooperative Apps reduce the need for Integration Platform-as-a-Service (iPaaS) offerings originally developed prior to the cloud era of API-based services and applications.

Back in the day (circa early 2000s) the first generation integration services, such as Enterprise Service Buses (ESBs), placed the “Integration Burden” squarely on the shoulders of an IT organization. Applications had not traditionally cooperated well with each other, requiring IT to implement very costly and expensive integration products. The ESB industry served a need when on-premise application dinosaurs ruled the software world, yet they will face the same fate as the on-prem applications they were originally developed to serve. They’ll be valuable in only the most complex use cases where on-premise and custom applications are prevalent.

The next generation of integration service enables application developers to build and deliver apps that instantly cooperate with each other.  A “cooperative app” works seamlessly with data that is mastered in other systems. For example, a common use case is connecting customer data from a CRM to lead data in a Marketing Automation system, with files and documents in Box, Dropbox or any of the leading cloud storage services.  Apps that “play nice” with other apps will move from preferred to required, as IT organizations and increasingly Line-of-Business Decision Makers will only select apps that fit with the other applications they’re using. The “Integration Burden” will strongly shift from the enterprise to the app developer and going forward, apps that don’t easily cooperate with other apps won’t survive.

Apps can “cooperate” and “play nicely.” While I can’t offer the same sort of manual for life with a three-year-old, I can recommend you take these 5 Steps in Building Cooperative Apps.

5 Steps in Building Cooperatives Apps

1. Start With Categories, Not Individual Endpoints
Your clients will always want options. Options are the delighters when it comes to building an optimal user experience. Knowing your app exists within a vast ecosystem of cloud services and applications your clients are already using, there’s vast opportunity to delight.

To start, identify the categories your application needs to collaborate with documents, CRM, Finance or Applicant Tracking Systems. Do this instead of focusing on individual endpoints. When you think in terms of a category, you consider use cases that broaden the options for your clients beyond designing to an individual endpoint. For example, you will have clients who have Marketing Automation services (the category) from HubSpot, Marketo, Eloqua, Salesforce and more (the endpoints,) so design your integration by considering the data objects and methods common to the category, not just one service. A category approach will have your app cooperating more quickly with a wider range of services, thereby expanding your market share.

2. Collect Data to Prioritize Endpoints Within Each Category
Next, start by supporting the services that will give you the broadest market reach.  At a leading job board in company based in the UK, their users’ data were primarily distributed among Google Drive, Dropbox and Microsoft OneDrive for cloud document storage. By collecting this data from the sales and business development team and organizing it into a single cloud document category, the priority individual endpoints became prevalent.

3. Draft Your Cooperative App Use Model
An application doesn’t exist on it’s own. Create a model that depicts the vast ecosystem of integrations at your organization, organized by the categories identified in Step 1 and the prioritized end-points you gathered in Step 2. Keep in mind that integration is a means to an end, and collaboration is your goal. The ideal user experience is an application seamlessly interacting with data your customer has stored in other applications while never leaving your app. Focus on the benefits your applications users will receive by cooperating with other apps in the category you selected.

Here’s a use case to hit this topic home: As a marketer, I want to promote, launch and execute a webinar on a leading web conferencing application. To make my life easier, I aim to have my email lists stored in our CRM, registrants tracked in the web conferencing app and activity cards updated back in the CRM as they attend the webinar. Furthermore, I’d like to share the presentation via Box after the webinar using our messaging platform. Integrating these applications enables me, as a marketer, to effectively generate new leads and convert to qualified opportunities for sales.

4. Develop Integration Use Cases
Integration use models typically follow a consistent pattern, and you can use this pattern to guide the definition of the user stories required to develop cooperative use cases for your application.  Note: “endpoint” is used to refer to the cloud application or service you’re connecting your application to. Discover your application’s integration pattern by evaluating these 10 dimensions of integration use cases:

1. Select – Where will my app present the user interface to select the endpoints the user will connect with your app?

2. Authenticate – How will I manage the authentication for each endpoint I’m connecting with my app? What type of authentication mechanism does the endpoint use (e.g., OAuth, SAML)? Where will I store and refresh the keys?

3. Objects – Which standard objects does my application need from each endpoint? What are the fields available for each data object?

4. Methods – Which methods do I want to support for each object? Determine which CRUD (Create, Retrieve, Update, Delete). How about Search capabilities?

5. Browse – How will users browse files and/or data from the endpoint?

6. Discover Custom Data – Do I need to discover custom data fields and custom data objects from the endpoints?

7. Map – How will I map standard and custom data objects and fields to my applications data model? WIll I give the user the ability to override my default settings for standard objects? How will I treat custom objects and data, and map that into my application’s data model?

8. Transform – Do I need to transform any of the data structures? Are formats for Date, Time and other values consistent?

9. Events & Synchronization – Are there events (e.g., changes to a data object) that my application needs to be alerted to?

10. Operations – Does my support and operations team need logging and usage data to support the integration? How will I handle alerts and notifications from the vendors regarding service outages, API changes, etc?

5. Build and Release an MVP (Minimum Viable Product)
Now that you’ve defined a broad set of integration use cases, it’s time to narrow the stories down into an iterative release plan so you can get your cooperative integration use model to market and gain feedback quickly.  Some typical considerations for MVPs include:

a. Implement read-only use cases first. Delay the create, update, delete user stories until later releases. Get the data moving between the apps first and then provide a means to update it later.

b. Initially include only standard data objects and standard data fields from the endpoint.

c. Provide a standard mapping of standard data. Provide the ability for the user to change your default data mapping and transformations in future releases.

d. Delay implementing more complex event handling and data synchronization scenarios until later releases.

 Your clients want to interact with the other apps and cloud services they’re using. Don’t inhibit them. Help them by making your app cooperative.

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The report, entitled “Social CRM Goes Mainstream,” suggests that CRM solutions should now include technologies that support business processes for acquiring, retaining, targeting, understanding and collaborating socially with customers. Business process professionals should design their future plans around that vision, it says.

Forrester believes that the social Web is forcing business process professionals to expand their thinking beyond the traditional two-way channel of communication between enterprise and customers to also include the interactions that customers have among themselves.

“CRM is evolving from its traditional focus on optimizing customer-facing transactional processes to include the strategies and technologies to develop collaborative and social connections with customers, suppliers, and even competitors,” it states.

Forrester vice president and principal analyst William Band and senior analyst Natalie Petouhoff contributed to the report.

The social trend has not gone unnoticed by CRM solution makers, both new and old.

New York-based startup Bantam Live is building its CRM platform around social CRM, and Salesforce has introduced a new capability called Chatter to its subscribers.

Social CRM was initially adopted by large organizations such as Comcast and Zappos on the customer support side, but also gives businesses the ability to listen and respond to the voice of the customer, said Bantam CEO John Rourke. That ability has shifted social CRM back to where CRM started: sales and marketing, he said.

The Twitter API made it possible for wide adoption of social CRM, and other social networks are copying its API functions to enable applications to pull in information, said Bantam CTO Henry Poydar.

Bantam uses its service to draw information from Twitter to discover new customer prospects, Rourke said. “We search for ‘Salesforce,’ and reach out to people, asking, ‘Have you considered us?’ “

Conversations are imported into a business process to create tasks for a sales team member to follow up with individuals, Poydar said. The company intends to introduce an API in Q2, and it will be integrating new project management capabilities into its platform.

Salesforce announced the integration of social CRM into its platform at the Dreamforce Global Gathering 2009 in December. Chatter is a layer of functionality that infuses social information into its existing application, said Salesforce’s director of platform research Peter Coffee.

“The most important thing to understand about Chatter is the tremendous recognition of the role of social networks as places people find each other and have important conversations,” Coffee said. “There’s also tremendous concern that there’s a downhill direction of sharing to people you know less and less well.”

Chatter leverages Salesforce’s existing governance and trust model to give customers the ability to look at and edit data items that are a coherent part of the architecture that customers already understand and use, Coffee added. “The architecture is based on well-defined APIs.”

“The world’s leading expert on your product or service probably doesn’t work for you anymore,” he said. “A customer has been forced by demands on their job to find a way to stretch your product or service in ways you may never have anticipated…Innovation is not limited to the producer of a product or service, but becomes a democratized process in which entire communities participate directly.”

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