We’ve just launched our agentic capabilities to make your AI workflows even more powerful. Read about it here →
We’ve just launched our agentic capabilities to make your AI workflows even more powerful. Read about it here →
Introducing Credal's multi-agent framework, designed to enable agentic reasoning and help enterprises use AI securely and effectively. Our mission at Credal is to harness frontier intelligence for the industries that have the power to make the world a better place. We work closely with highly regulated organizations that are vital to human welfare to understand their world and deliver a product that can transform their business operations.
Enterprises trust and depend on us. We are built from the ground up with Enterprise needs for Generative AI security, governance, and privacy at the forefront, which is why institutions as large as the US Department of Health and Human Services or as critical to global infrastructure as Transferwise, MongoDB, and the IFRS trust us as their internal AI platform.
We have given thousands the power to build what they conceive. Now, we are bringing some of the innovation our customers have helped us incubate to the world.
Credal customers have deployed hundreds of agents capable of deeply understanding their Enterprise’s data and their employees’ expertise while also possessing the power to gradually, and significantly, improve over time. While these monolithic agents continue to drive massive ROI for our customers, we know that “Chat with your data” will not scale with operational complexity.
In order for Credal to meaningfully transform businesses, we needed to build a framework that could connect AI agents with companies’ internal systems and each other.
Our framework solves the following 3 problems we have identified and believe are unsolved:
Let's dive in.
The Credal Agentic Framework features independent, specialized Agents that collaborate with each other to complete complex, nested requests. Each Agent is crafted by subject matter experts - your employees - for specific tasks such as researching a potential prospect, answering a seller’s question about a product line, conducting KYC and AML checks, answering employee HR questions, and more. Each Agent, when invoked by a user or API call, can request assistance from other Agents to complete their task, while respecting the underlying permissions of data and actions of the original invoking user. This composability goes beyond monolithic AI deployments, allowing you to achieve more powerful Agents while still putting enterprise governance, risk, and compliance concerns at the center of how Agents get deployed.
Every user request in Credal now follows this pattern:
This functionality is the foundation of workflows built in Credal.
AI today is more than just search. LLMs have the ability to not only regurgitate the information with which they were trained, but they now possess the power to reason. They can think step by step.
LLMs’ reasoning capabilities are only getting better, opening the doors for Enterprise agents to make decisions and take actions - all while adapting based on past interactions and feedback.
Credal’s agents use state-of-the-art techniques to leverage short term memory (the conversation so far), long term memory (all of the Enterprise’s data and tools), and your employee expertise to complete Enterprise user requests. To make context aware decisions, Credal Agents identify and consult with your Subject Matter Experts on any given topic. To provide full visibility into these decisions, we document a full audit trail of the series of steps taken by Credal Agents, shipped with debuggability and proper justification as to why each was taken.
As a result, Credal now has agency, the power to use given resources to decide how to make progress towards a goal.
The "Actions" component of the Credal Agentic Framework refers to the specific functionalities or tasks that each Agent can execute. These actions are built to be reusable and can be combined to create custom workflows. This modularity allows companies to design their enterprise solutions with flexibility and adapt to emerging requirements without overhauling entire systems.
Our Open Source Actions Library features a set of pre-built, well-tested Actions that cover common enterprise workflows without needing to build from scratch. These Actions are continuously improved by the community, reducing maintenance overhead as APIs evolve. Some examples of out-of-the-box actions we support:
We are only getting started, and this list is the tip of the iceberg for what you can expect. We hope that Credal builders will be able to collaborate and share ideas about how they are enabling their Enterprises to connect their systems with Credal Agents.
Additionally, we support configuring inputs and authentication for hitting custom API endpoints to connect to your private, internal systems. If you have resources that you do not want the world to know you use, we will support that by allowing you to run the arbitrary code in order to accomplish your work.
Once you've chosen your underlying Action, we give you the ability to contextualize it (provide company-specific documentation) before you publish them for org-wide use. This establishes a currying system that abstracts away the nitty gritty technical details from non-technical folks. Think “update confluence page” → “Update the HR Policy.” Suddenly, building AI powered operations with API calls is democratized for anyone at your organization, even those who don’t need to know what an API is.
Credal Agents have the ability to call upon each other built in. By abstracting away the problem of providing consistent authorization across the full chain of calls, we allow you to break up complex operations into more specific and manageable components, which can individually be made extremely reliable and then collectively stitched together to accomplish multi-step operations.
We enforce inter-Agent authorization to ensure secure and controlled communication between autonomous systems through proper identity verification and permission protocols. This framework prevents unauthorized access while enabling seamless collaboration between trusted agents across your organization. Owners of any given resource can view, add, and revoke access at any time.
Our system provides comprehensive visualization tools that make complex agent decision trees transparent and easy to understand at a glance. Users can customize reasoning depth constraints according to their specific use cases, allowing precise control over how deeply agents can explore interconnected decision processes.
Our Governed Agent Framework’s composability, governance-first design, and human-centric self-improvement loop represents the state of the art in accurate, highly specialized, compliance-ready agentic capabilities for Enterprises.
Credal’s approach diverges from other solutions on the market by providing multiple targeted agents that can each be precisely evaluated, optimized independently, and can consult each other when needed, seamlessly leveraging reasoning models, internal and external data sources, and employee expertise.
We aim to target a variety of complex and mission-critical business areas — from lead generation and scoring, to HR processes, to operational tasks like quarterly earnings prep and fraud detection.
Credal is live and used in production by customers (who include Fortune 50 enterprises, US government agencies, tech giants and some of the fastest growing startups in the world) for many use cases. Here are some examples of the problems they're solving using Credal today:
Please reach out to the Credal team at support@credal.ai with any questions.
Credal Agents are designed to be carefully governed, evaluated, and improved. An emphasis on secure, rules-based governance sets Credal apart from solutions that may offer extensive AI capabilities but lack robust compliance or oversight mechanisms. Our framework’s overt alignment with enterprise risk and compliance needs (e.g., negative news checks, KYB) underscores this difference.
We understand the nightmare that an AI Agent posting Jira tickets willy-nilly could create. Your enterprise’s operations are specific, intentional, and require strict rules and context to be executed well. To that end, many Agentic actions will require human oversight and approval. Credal allows you to control who can check off which actions before they’re executed. Reviewers will be able to trace down all necessary details to defend why the Action needs to be made, and confidently “Approve” or “Deny” the request. Critically, Credal also enforces permissions in the original source systems, meaning users can never read or edit data that they don’t already have permission to in the underlying source system.
In the Credal app, you can see all Audit Logs for invoked Actions, why the Action was invoked, who approved the invocation etc. Traceability of the full chain of decisions made by an Agent provides total visibility and control back to the Enterprise over how these Agents are behaving, as well as providing Users the ability to provide feedback at each step on the journey, providing a compounding data Asset that improves each Agent with each invocation.
One of our key value offerings is that your intelligent systems in Credal will gradually improve themselves and your operations over time. Specifically, these Agents will understand your enterprise documentation extremely well, identifying gaps in information and automatically enriching internal wikis.
To give you confidence in these systems, the Credal Agentic Framework comes with tools to zoom into each and every decision made by Agents, see why they were made for debugging purposes, and provide feedback if something looks good or bad.
More on this coming soon! Stay tuned. Please reach out to support@credal.ai with any questions.
Credal gives you everything you need to supercharge your business using generative AI, securely.
