Cognium AI Studio

AI Orchestration Platform

Automate structured work with
AI agents you can trust in production

Cognium is an AI orchestration platform for document review, evidence gathering, multi-step approvals, and any structured business process. Built on Microsoft Power Platform, deployed in your own tenant, with the audit trail and governance that real production work needs.

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THE GAP

Workflow tools weren't built for AI judgement. AI tools weren't built for production.

Generic workflow platforms can call an AI model from inside a flow, but treat it as one more step among many. Generic AI tools can reason brilliantly, but leave you with no audit trail, no way to test changes before they go live, and no way to correct the AI when it gets something wrong. Production work in regulated, finance, operations, or risk-sensitive functions needs both.

WHAT COGNIUM IS

An AI orchestration platform built around how frontier AI is actually meant to be used

Every Cognium workflow is an AI agent with a bounded scope, a structured output contract, and a full audit trail. Workflows can chain together. Outputs can be reviewed and corrected by humans. Nothing reaches production without passing simulation testing. The same architectural patterns that make modern AI systems reliable, applied to your business processes.

WHY NOT JUST A POWER AUTOMATE FLOW?

You can build an AI flow in an afternoon. Production-grade AI requires much more.

A Power Automate flow with an AI Builder prompt works well for one-off summaries and simple automations. It is not built for work that has to pass audit, run reliably for a long time, or be defended to a regulator. Here is what changes when AI moves from convenience tool to production system.

Capability

Power Automate + AI Builder

Cognium AI Studio

Who builds and tests

Who owns the prompt and the test cycle

Developers. Every prompt change is an IT change request. Business users describe the requirement, developers edit the flow, re-test, and republish. Slow cycle, IT budget.

​​Business users. Business users write prompts, run their own simulations, and approve workflows. No code, no IT bottleneck. Prompts are domain content, not code. Business users own them directly.

Testing before going live

Catching errors before they reach production

Not mandatory. Ideal practice is developer and business user pairing on test sample files, but nothing in the platform enforces it. Publishing without testing is always available.

​​Mandatory and business-user-owned. Workflows cannot go live without passing a Simulation Plan run by the business user. The plan stays attached forever as audit evidence.

Versioning and change control

What ran six months ago

Manual. You save copies of the flow yourself, track prompt changes in a spreadsheet, name versions by hand, and remember which one ran on which date. Easy to get wrong, easy to lose.

​​Out of the box. Every change creates a new version. Approval automatically freezes a snapshot of the prompt, model, and dependencies. Cannot be bypassed. You can prove exactly what ran on any date.

Audit trail of AI decisions

Defending to a regulator

Not retained by default. Run history shows the flow executed. The AI's reasoning, source citations, and confidence are not preserved unless you build custom logging.

Full bidirectional audit chain. Every intake event, every AI call with original request and response, every reasoning step, every reviewer correction, every downstream action. Linked end to end, retained automatically.

Correcting AI mistakes

When the AI gets it wrong

No formal correction path by default. Wrong AI output goes to Teams or downstream actions and stays wrong. A review step can be built in, but is not part of the platform.

​​Built-in reviewer correction. Reviewers correct the AI's output. Corrected output becomes the operational truth for downstream automation. The original AI response is preserved for audit.

AI model choice

Vendor lock-in risk

Hardcoded per flow. The model used by a Power Automate prompt is fixed at build time. Additional models can be plumbed in through Azure AI Foundry, but every change requires developer work.

AI model agnostic. Anthropic, Google, Azure OpenAI, OpenAI, or self-hosted. Business users choose the model per workflow and can manage model selection inside the workflow itself. Version locked at workflow approval.

Governance and ownership

When the maker leaves

Possible but manual. ALM and proper deployment can be set up with effort, but flows often end up in one user's My Flows. Breaks or becomes orphaned when they leave unless governance is enforced manually.

Deployed solution with ALM by default. Same governance as any production Power Platform or D365 build. Dev, UAT, Prod environments built in.

Best fit

When to use which

One-off summaries, internal automation, low-risk convenience tasks. Fast to build, fine to lose.

​​Production AI in regulated organisations, finance, operations, or risk-sensitive functions. Where the AI's answer matters and must be defended.

A Power Automate flow is a great way to get an AI summary into Teams. Cognium is what you reach for when the AI's answer has to stand up in front of a regulator, an auditor, or a board.

Different tools for different stakes. We are not replacing your Power Automate flows. We are the production layer for the AI work that actually matters.

01

Bounded AI agents

Each workflow is a focused agent doing one structured task with a defined output schema. No sprawling prompts. No unpredictable behaviour. The architecture that makes AI safe to put in production.

02

Full audit chain

Every intake event, every workflow run, every AI call, every action taken. Linked bidirectionally so you can walk forward from a file that arrived or backward from any decision made. Real audit, not theatre.

03

Humans in the loop, by design

AI flags, humans determine. Reviewers can correct the AI's output, and the correction becomes the operational truth for downstream automation. The original AI response is preserved for audit. You get speed without giving up control.

04

Frozen at approval, immutable in production

When a workflow goes live it is locked against a snapshot of its dependencies. Later changes to the AI model or downstream actions cannot silently affect the workflow. The definitive answer to "what happens when the AI changes".

WHO USES IT

Built for the work humans should not be doing manually

Heads of operations, automation, and digital transformation use Cognium to take structured, document-heavy, judgement-required work off their teams' plates, without the unpredictability that has kept AI out of production until now.

DOCUMENT REVIEW

Reading and assessing at scale

Policies, contracts, applications, reports, evidence files. Anywhere a person currently reads documents against a set of criteria and reaches a structured conclusion.

EVIDENCE LIFECYCLES

Gathering, assessing, chasing

Requesting evidence, assessing what arrives, chasing what does not, escalating when needed. The full lifecycle as orchestrated workflows, not a separate workflow tool.

MULTI-STEP APPROVALS

Sequenced AI and human checks

Chain workflows together: extract from one document, reason across several, route the result to a human for sign-off. Each step independently auditable.

HOW IT FITS

Sits inside your Microsoft tenant, works with what you already have

Cognium is built on Microsoft Power Platform and Dataverse. It deploys into your own Microsoft 365 tenant and works with the Microsoft tools your team already uses every day.

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Your tenant, your data

Deploys into your Microsoft 365 tenant. Your data stays in your environment. Olgtech is outside the data flow.

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AI model agnostic

Anthropic, Google, Azure OpenAI, or your own self-hosted model. You choose the AI, you sign the agreement, you control the spend.

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No per-user fees

Unlimited users. Your whole team has access without licence cost scaling with headcount.

SEE IT WORKING

Cognium doing the work, end to end

Three short videos showing Cognium reading real documents, reasoning against real regulations, and producing audit-ready findings. No staged demos. The platform doing what it does.

SAMPLE USE CASE

Regulated compliance

Cognium's lead application is regulated compliance work, the domain where bounded AI agents, full audit chains, and human-in-the-loop correction matter most. Everything below shows how the platform handles financial services and public sector compliance use cases.