ColleagueAI helps finance, operations, risk, compliance, legal, procurement, HR and service teams deploy AI agent packages with clear ownership, risk classification, ROI evidence and audit trails.
ColleagueAI helps enterprises deploy AI agents with governance built in. Each agent is classified with the CAI Score, supported by documented controls, and delivered with evidence you can review. Agents run in your own environment; ColleagueAI provides the governance control plane.
ColleagueAI packages are designed for deployment inside the customer Microsoft and cloud boundary. Customer business data stays in the customer-controlled data plane; ColleagueAI provides the agent blueprint, CAI Score governance pattern, deployment guidance and versioning support.
The runtime, identity checks, retrieval and audit evidence are deployed against the customer environment.
We package the repeatable agent design and governance controls so teams do not start from a blank prompt, workflow or audit model.
RAG patterns should inherit the user’s existing Entra ID and M365 permissions. The agent should only retrieve or summarize content the user is already authorized to access.
L3 and L4 packages are designed with review, approval, escalation and audit evidence patterns.
AI Act and regulated-use classification depends on customer process, data and deployment context. This is governance evidence, not a legal compliance guarantee.
Each package combines a deployable agent blueprint, implementation guidance, ROI support, governance evidence, and a CAI Token Economy Monitor.
Each ColleagueAI agent package includes a deployable blueprint, CAI Score classification, implementation guidance, ROI support, audit evidence, and token-economy indicators for your Microsoft/Azure environment.
Validate the agent on your own cases before go-live. The business case is built from practical inputs: time saved, effort reduced, FTE capacity released, and estimated payback.
Each package includes a CAI Score risk tier, a named human accountability model, and audit evidence designed to support risk, compliance, and procurement review.
The hard part of enterprise AI isn’t building an agent that works in a demo, it’s governing the sprawl once dozens of them are live: knowing where each one is allowed to act, who’s accountable when it does, and being able to prove it to an auditor. Colleague AI gives you that framework first (the governance blueprint) then fits certified agents into it at the right tier.
The blueprint comes first: every step of your process gets the CAI tier it's allowed to operate at, and each slot is filled only by an agent certified at or below that tier. Agents fill slots in a governed design, they don't get bolted onto a process and hope for the best.
An agent's CAI tier is a hard contract about its autonomy. Low-tier agents only draft and suggest. High-tier agents assist a named human who stays accountable. Safety is structural, not a marketing claim.
Agents run inside your own Microsoft and cloud environment. Colleague AI hosts the control plane, governance metadata, configuration, scores, audit trail, entitlements, and partner-registration records. In production deployments, customer operational data is designed to remain inside the customer tenancy. Public website demos, forms, partner registrations, and other submitted website inputs are separate ColleagueAI-hosted flows and should not be used for confidential production data.
We prefer evidence over claims: defined tiers, named accountability, operating controls, and audit records that can be reviewed.
Colleague AI is built by people who have run regulated finance, insurance and SAP operations, and sat through the audits that follow. The CAI Score encodes how those functions actually reason about risk and control, not how a demo looks.
The CAI Score is an open framework: defined tiers, named human roles, logging and review periods. You can see exactly how every agent is classified, and push back if you disagree. A methodology that holds up to scrutiny is one you can actually stand behind.
Agents run in your tenant; we do not process your customer data. Actions are logged and attributable, and the evidence is designed to support governance and compliance review.
The higher the tier, the more an agent can do. The controls also increase: human oversight, logging, review points, and named accountability.
Informs and answers. Takes no action and changes no record. The human does the work; the agent just makes it faster to find and understand.
Produces a work product (a document, a query, a report, an outreach message) for a human to review and approve. Nothing the agent makes is used until a person signs off.
Executes routine, low-risk actions inside a bounded workflow, classify, route, fulfil, log. Exceptions and anything unusual are handed to a human. Every action is time-stamped.
Supports decisions and controls in higher-stakes processes, compliance, contracts, security, four-eyes. A named human remains accountable for the call; the agent assists and evidences it. Built for high-risk-process scrutiny.
Acts independently within hard, pre-approved guardrails. Reserved for the highest level of certification, and not used by any agent in this catalogue today.
// This catalogue ships at L2-L4. L4 agents require senior sign-off before go-live.
Filter by function and autonomy tier. Open any package to review the workflow fit, value case, KPI impact, oversight model, and risk & compliance posture.
A single agent can remove friction. A governed sequence can improve an end-to-end process, with each agent operating at the right tier and humans owning the high-stakes steps.
From unexplained reconciliation breaks to a board-ready report, with dual control on the numbers that matter.
An escalation arrives and ends up, weeks later, as a clean line in the monthly client pack, without a manager living in the ticket queue.
A vendor MSA goes from inbox to signature with the obligations understood and the risks flagged, legal time spent on judgement, not reading.
A risk event is captured cleanly, oversight stays continuous, and the audit deadline never sneaks up, with a live dashboard instead of a spreadsheet scramble.
Choose an agent, enter your own assumptions, and estimate annual savings, hours released, FTE equivalent, ROI, and payback. Your figures stay in your browser.
Estimate only. Figures are generated from your inputs and editable default assumptions (annual full-time hours taken as 1,840). They illustrate potential value and are not a guarantee, a quote, or financial advice.
Agents run where your business data already lives. ColleagueAI holds the governance metadata, scoring, audit evidence, and token-economy indicators around them.
Agents run inside your Microsoft Copilot Studio, Power Automate and Azure estate. Colleague AI hosts only the control plane, scores, policies, audit metadata. No customer data ever touches our side. Your data stays in your walls.
The CAI tier defines exactly where a person stays accountable. L4 agents never decide alone, they assist, evidence, and hand the call to a named human. Oversight isn't a setting you can switch off; it's built into the tier.
Every agent action is logged, time-stamped and attributable. When an auditor or regulator asks what happened and who approved it, the answer is already a record, not something you piece together after the fact.
Risk classification, human oversight, logging, and transparency are core to the CAI Score. The framework is designed to support EU AI Act, DORA, and ISO/IEC 42001 evidence work, subject to client implementation and legal review.
Six questions. Get your organisation's AI governance maturity level, and the specific gaps to close before a regulator or auditor asks. Built on the same CAI methodology we certify agents with.
Indicative self-assessment. Your answers stay in your browser, nothing is sent or stored.
Direct answers on the CAI Score, deployment, EU AI Act alignment, and how the trust layer differs from an agent management platform.
Colleague AI is the trust layer for enterprise AI. It certifies AI agents against the CAI Score, a five-tier risk classification (L1-L5), documenting each agent’s controls and producing an audit trail. Agents run inside your own environment; Colleague AI hosts only the governance control plane, so enterprises can deploy AI they can defend.
The CAI Score is a certification framework for AI agents, described as “the FICO of AI.” It classifies each agent by risk on a five-tier scale, from L1 (Assist) to L5 (Autonomous), defining exactly how much the agent does on its own and where a named human stays accountable, then evidences it for audit.
L1 Assist: informs only, takes no action. L2 Draft: produces work for a human to approve. L3 Operate: executes routine actions inside a bounded workflow. L4 Decide (supervised): supports high-stakes decisions with a named accountable human. L5 Autonomous: acts within hard, pre-approved guardrails. The higher the tier, the more oversight and logging the framework requires.
Agents run inside your own Microsoft Copilot Studio, Power Automate and Azure environment. Colleague AI hosts only the control plane, scores, policies and audit metadata. No customer data is ever processed on our side. Your data stays in your tenant.
Yes. Risk classification, human oversight, logging and transparency are the core of the CAI Score, and they track directly to the EU AI Act’s obligations for high-risk AI. General-purpose AI obligations apply from August 2025 with high-risk rules close behind, every agent ships already aligned, so adoption doesn’t outpace compliance.
Most platforms observe and orchestrate agents (the control plane) or audit models after the fact. Colleague AI adds the missing layer: a portable risk score and certification for every agent (the CAI Score) plus production-grade agents that ship pre-certified. It is governance you can act on, not just another dashboard.
Agent sprawl is what happens when AI agents multiply across an enterprise faster than anyone is tracking them, different vendors, frameworks and clouds, each with its own risk profile and no shared audit trail. Giving each agent a CAI Score certification means every one has a known tier and an evidence record, so you always know what you’ve got running and who owns it.
The catalogue includes 36 production-grade AI agents across five functional pillars: Operations & Service Delivery, Risk, Security & Compliance, Data & Infrastructure, Sales & Marketing, and Corporate (HR, Legal, Procurement, Reporting). They run at CAI tiers L2 to L4, with L4 agents requiring senior sign-off before go-live.
This static walkthrough uses a fictional finance case to show the operating model behind ColleagueAI packages: permission-aware retrieval, root-cause analysis, human oversight, and an evidence trail suitable for review.
This positioning is intentionally cautious: ColleagueAI describes governance support and deployment readiness, not a blanket legal compliance guarantee.
Use this page to choose a business use case, understand the governance profile, review the agent factsheet, and request a demo. Production access is released through a guided demo and commercial setup.
Bring our certified agents to your network or your clients and earn a share of what you bring in, refer, resell or deploy, with brand-safe assets and tracked attribution. We sell direct too; partners extend the reach.
Become a partner →CAI Token Economy Monitor
Every ColleagueAI agent package can include token-level usage intelligence that runs inside the client environment. It helps customers see token consumption, estimated cost, retries, oversized context, model choices, and optimisation opportunities, without ColleagueAI seeing prompts, outputs, documents, or business content.
This is not employee surveillance. It is client-owned AI cost intelligence: metadata that helps users, finance, operations, and leadership reduce token waste and scale the agents that deliver value.