Company
An engineering company for autonomous AI systems.
CONFegitech is an AI technology and engineering company focused on autonomous agents and intelligent systems. This page says what we are trying to do and how we intend to work, and nothing about history we do not have.
Mission
To develop intelligent systems that combine reasoning, planning, tool usage, execution, verification, and appropriate human oversight to solve complex technical and operational problems.
Vision
To advance the engineering of AI systems capable of moving beyond conversational responses toward useful, goal-oriented execution.
Engineering philosophy
Six beliefs that shape the work.
- The model is a component, not the system. Reliability comes from the architecture around the model: planner, tool contracts, runtime, verifier, controls.
- Tool access is a privilege, not a default. Agents request. Policy decides.
- “Done” must be defined before work starts. Completion is something checked, not something announced.
- An unobservable agent cannot be trusted or improved. Every step should leave a trace that people can inspect.
- Failure is the normal case to design for. Recovery, bounded retries and safe stopping are first-class behaviours.
- More agents is not more intelligence. Multi-agent designs need explicit coordination and evaluation, or they multiply error.
Approach to autonomous systems
Plan, act, verify, inside boundaries.
We treat an agent as a loop: interpret an objective, plan, choose tools, execute, and check the result against criteria defined at the start. How much such a system may do on its own depends on the task, the permissions it holds, the strength of its verification and the cost of a wrong action.
We do not claim that autonomous systems can perform every task without supervision, and the work is organized around the cases where they cannot.
Responsible autonomy
Principles we work to
- Permissions are explicit, scoped to the task and expire with it.
- Consequential actions need human approval, with evidence attached.
- Results are verified before a task is reported complete.
- Runs are logged so they can be inspected, audited and improved.
- Task data follows defined scope, retention and deletion rules.
- We state maturity plainly and never present a proposal as a product.
Technology focus
Where the engineering is aimed.
Six focus areas: planning, tool use, adaptive execution, context and memory, verification, and controlled autonomy. In three horizons that are directions, not a roadmap.
- 01 · Foundation
The reference model, its interfaces and the principles behind them, published openly so they can be questioned.
- 02 · Exploration
Prototypes and evaluation methods that test the model against concrete tasks, with recorded runs and stated limitations.
- 03 · Extension
Dedicated technologies built on what the earlier work supports. Nothing here is promised or dated.
Collaboration
Ways to work with us.
AI engineering projects
You are designing or evaluating an agent system and want to think through architecture, tooling or reliability.
Start this conversationResearch discussions
You want to discuss an open question, an evaluation method or an experiment design.
Start this conversationTechnical partnerships
You work on complementary technology and want to explore working together.
Start this conversationBusiness collaborations
You are asking whether a particular workflow is a good candidate for an agent.
Start this conversationContact
Start a conversation.
Tell us the problem you are working on. We will say plainly whether it is one we can help think through.