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2025 will undoubtedly be the year AI Agents become real. However, many early market entrants tend to be either single-minded and less flexible, or more horizontal but focused on IT and developers (and therefore not always business friendly).
To start up Sema4.ai says it has the differentiator that forward-thinking businesses need: the company has put a “tremendous amount of intelligence” into its platform to make it suitable for a wide variety of business cases. commercial use.
“We think it’s much better to have a horizontal platform for companies to build their agents for, rather than coming in with a single focus,” said Rob Bearden, co-founder and CEO of Sema4.ai , at VentureBeat.
Today, Sema4.ai announces the general availability of its full-stack enterprise AI agent platform. In less than 9 months, the startup came out of hiding, piloted its platform with six Fortune 2000s, secured $30.5 million in financing and acquisition of an open source automation company Robocorp. And it has already been featured in two Gartner hype cycles.
“Agents are going to drive the greatest transformation in business models and efficiencies that enterprise has seen since the Internet began,” Bearden said.
AI agents outside of DevOps and IT teams
The no-code of Sema4.ai agent platform was designed to “speak the language of industry” and integrate with existing business processes and applications. It has seven key elements:
- Studio: Users can quickly build, test, and deploy AI agents.
- Runbooks: Users can create and manage agents with natural language runbooks and predefined actions.
- Control Room: Provides complete lifecycle management as well as security and scalability.
- Actions: An automation framework that allows agents to integrate with applications like SharePoint, SAP, and APIs using Automation as Code and Python.
- Workroom: Users can search for, work with, and supervise enterprise agents.
- Document Intelligence: Provides accurate interpretation of documents.
- Dynamic Data Access: Gives agents copyless access to past, present and future data.
Evolving the current operating model from “programmatically driven by DevOps and IT” toward the business user is critical, Bearden emphasized. This is because business users fully understand specific processes and procedures, best practice results, and potential issues and resolution methods.
In Sema4.ai, business users can define parameters and expected results in runbooks that calibrate the AI; agentswith an understanding of the data they need and the best reasoning paths, then build automations and software development kits (SDKs).
“Everything is driven by the business user in natural language,” said Bearden, former CEO of the data platform company. Cloudera. “Agents will disintermediate legacy ERP applications and even SaaS applications. They will put the power in the hands of the business user rather than DevOps and IT teams.
The Sema4.ai platform is designed to be interoperable with the most cost-effective Large Language Model (LLM) for the enterprise use case – currently including ClaudeOpenAI, Azure and Bedrock, but it will be expanded, Bearden explained.
“Bring your own LLM, we will make sure to interact with it at the highest level,” he said.
Use Case: Koch Invoice Reconciliation
Customers have used the Sema4.ai platform for a range of use cases, from simple scenarios requiring a single agent for a specific use case, to “15, 18, 20 and more” working in collaboration to manage entire business processes, Bearden explained. Agents (at least for now) are best in areas where the work is procedural, high-volume, human-intensive, understood, measurable, and delivers definitive results.
“It’s typically a high ROI job,” Bearden said. “It’s measurable. It’s verifiable.
Six Fortune 2000 companies are testing the platform as part of an initial proof of concept (PoC). Bearden explained that these partners use agents to automate invoice processing, payment reconciliation, employee onboarding and regulatory compliance. In two of the PoCs, the Sema4.ai platform autonomously performs more than 80% of the knowledge work tasks.
One of the first to adopt it is the industrial giant Koch, which use agents to automate one of its invoice reconciliation processes, Koch Labs principal Tanner Gonzalez told VentureBeat. Previously, he explained, this involved manually reviewing invoices that could be 80 pages or more. Sema4.ai allows them to use natural language processing (NLP) to create automated workflows that extract relevant data and validate invoices.
The main advantage of the platform is that it provides an easy-to-maintain, document-like interface for creating and updating AI generation workflows. “Compared to previous robotic process automation tools we have used, Sema4.ai is much more user-friendly and does not require specialized technical skills to manage over time,” Gonzalez said.
Using natural language, employees (financial analysts, accountants, operations engineers, or other non-technical people) interact with the platform in the same way they would describe their workflow in a Word document, “explaining their logic and the tasks they complete over and over again, “explained Gonzalez. In more complex use cases, the platform offers data scientists the ability to deploy custom AI models and data engineers to connect new data sources for read and write functions.
Looking ahead, Koch sees potential to expand the platform’s use to other areas such as market research analysis or external communications for sales teams, Gonzalez said. “The flexibility and low-code nature of the platform makes it well suited to address a variety of automation and conversational AI use cases within our organization,” he said.
A horizontal approach to meet a variety of business needs
When looking to adopt AI agents, Koch analyzed many alternatives in the market, Gonzalez noted. They found others focused too narrowly on specific industries, building their own core models or limiting themselves to integrations.
The main strengths of Sema4.ai, he said, are 1.) flexibility, “meaning we are not tied to a specific model as new ones emerge”; 2.) ease of use for business users who can write down their steps instead of coding or learning a new tool; and 3.) the ability to implement closed-loop automation, driving true agent automation and periodically monitoring progress for new anomalies.
Navin Chaddha, Managing Partner at Mayfield Fundone of Sema4.ai’s major backers, said the startup has a “mission to build the agentic enterprise” and “pioneer the future of knowledge work” with capable AI agents to perform complex tasks with precision, efficiency and autonomy.
“Their platform brings real value to businesses and will be key to powering the era of human-AI collaborative intelligence,” he said.