Agents that work for your company, within its rules.
We design, build and operate specialist agents for your business. And we allocate agents coming from other platforms and vendors to the same teams. Everything goes through the EDAVEN Organization & Agents hub.
- Agent
- Inventory monitor
- Effect
- Reviewable write
- Accountable
- Operations, accepted by name
- Limit
- Reorder point, 4 stores
- Review
- Another person, after the act
- Proof
- Company record
Every agent is born governed.
AI and agent governance is not a separate project, nor a policy document. It is part of each agent’s architecture, engineering and operation from day one, and every rule is applied to every act while the agent works.
Gartner expects more than 40% of agent projects to be canceled by 2027 because of cost, unclear value and gaps in risk management. Gartner, Hype Cycle for Artificial Intelligence, 2026
In the architecture
Policies and risk
- An inventory of agents, models and third-party AI
- Risk classified per case, with the control it requires
- Purpose, owner, team and a limit accepted by name
- Only data with defined origin, purpose and retention
- Only models approved for that type of data
In the engineering
Security and quality
- Its own identity and mandate for each agent
- Actions outside the mandate denied before they run
- Adversarial and bias tests, and tests for the known risks of agent applications
- Vendor agents qualified on entry and again when they change
- A person reviews and signs each version before use
In the operation
Oversight and audit
- Another person reviews what carries risk; dual approval for high risk
- A stop condition and who authorizes resuming
- Monitoring of drift, exceptions and consumption, with a cost ceiling
- Incidents handled with an evidence package
- A receipt and provenance for every act; autonomy that rises and falls with the track record
And the learning stays with the company: human-curated memory, in your environment, outside the vendor’s model.
Controls are linked to the frameworks auditors and customers ask for: the EU AI Act, GDPR, ISO/IEC 42001, the NIST AI RMF and OWASP for LLMs and agents. This is a reference mapping, not legal advice or certification. See governance in detail
Three layers, each with one question
It is the same split the market uses for agent platforms. The difference is in the top layer.
Organization
Who answers for it?
- People, teams and agents on one map
- An owner for each agent
- A limit accepted by name
- Cost per piece of work and company memory
Agent control plane
May this act happen?
- Agent identity
- The shape of each act and how much human attention it needs
- Review by another person when there is risk
- A receipt for every act
Agent runtime
Where does the work run?
- In the work tool, as a plug-in
- In your environment
- On the data platform
- At the agent vendor
How an agent is born
Nobody writes code to create an agent. The business specialist talks to the EDAVEN Builder Agent, which always comes with the Organization & Agents module and prepares each step. No agent goes into use without a person’s signature.
Purpose
What it is for, who it works for and what it must never do.
Shape of the effect
Whether it only queries, writes something a person reviews later, or proposes and waits for approval.
Data and tools
Only data with a usage agreement and only tools that fit the limit.
Model
Among the models the company has cleared for that kind of data.
Proof
Test cases, including the known risks of agentic applications.
Signature
A person reviews and signs. Only then does the agent get work.
Agents of any origin, on the same team
The hub does not require everything to be built by us. It takes in agents from wherever they already exist and puts them all under the same rules.
The ones we build
Specialists for your business, from an industry template.
How it comes in. Born in the hub, with an owner and a signature.
Plug-in
The same specialists, running where people work.
How it comes in. Registered installation. Revoking switches it off everywhere.
From other vendors
Third-party agents the company already uses or wants to use.
How it comes in. They come in through the vendor’s public card and get an internal owner. If the vendor changes the agent, it goes back through qualification.
From platforms
Assistants from the data and AI platforms the company uses.
How it comes in. What they find comes in as context, with its origin recorded, for whoever decides.
The shape of each act
Every agent act takes one of three shapes. The shape says how much human attention it needs, and it is the same across the product.
Autonomy that is earned
An agent starts with little autonomy. It goes up when someone grants it, based on the agent’s track record, and drops again when the work gets worse. Being on a team gives no one, person or agent, the right to approve.
- QueryReads and answers. Changes nothing.
- Reviewable writeExecutes, and a person reviews afterwards.
- Proposal with approvalOnly happens once approved.
What Arcogi delivers
- Architecture
- The design of the teams of people and agents, the limits of each one and the links to the platforms the company already has.
- Engineering
- Building and qualifying the agents and connectors, with the business specialist.
- Operation
- The day to day: adjusting autonomy, reviewing what needs review and retiring what is no longer useful.
Every project starts from what the company already has. We do not promise gains before measuring.
Which agents already work in your company?
In half an hour, Matias helps map what already runs and where to start organizing.