Build · AI agents & software
Agents, knowledge, and software that run where your data lives.
AP0110 builds AI agents, knowledge systems, and production software that run where your data lives — model-agnostic and deployed on infrastructure you own. We design agentic systems with tools, memory, and guardrails, private retrieval (RAG) over your own documents, and the web platforms and data-driven applications around them — engineered to standards and handed over clean, with no lock-in.
What we build
From a single agent to a private second brain
Agentic systems, private knowledge, and the production software around them — grounded in your own data and owned end to end. Bring any model, or none; own where it runs.
Agents that run where your data lives
We design agentic systems — tools, memory, planning, and guardrails — that act on your behalf inside your own environment. No data leaves your jurisdiction, and the agent only does what its guardrails allow.
Private knowledge & retrieval (RAG)
Turn your documents, records, and institutional memory into a connected, searchable knowledge base — a private second brain. Retrieval-augmented generation grounds every answer in your own sources, with citations, running entirely on infrastructure you control.
Model-agnostic by design
Bring any model, or none. Self-host open weights or connect a managed model you already use — and swap freely as the frontier moves. No lock-in to one vendor’s roadmap, pricing, or API.
Guardrails & observability
Every agent action and retrieval is logged for audit, access is least-privilege by default, and humans stay in the loop on consequential decisions. You can verify what the system did rather than having to trust it.
Applications people actually use
Copilots, assistants, and workflow automation embedded in the tools your teams already work in — accessible, fast, and engineered to standards, then handed over clean with no lock-in.
Integration with what you run
Agents connect to your existing data systems and tools through open standards like the Model Context Protocol — so AI augments the stack you have instead of replacing it.
Production software, shipped
Beyond agents: fast, accessible web platforms and data-driven applications — engineered to standards, reviewed and tested, then handed over clean with no lock-in. The software you depend on, built by people accountable for it.
How our agents earn trust
Architected to be understood
Most AI agents are opaque chains you have to take on faith. Ours are built so every step is readable, reviewable, and yours to keep.
Glass-box, not black-box
Every step your agent takes is captured as something a human can read — not a hidden chain of prompts. Interpretability is a property of the architecture, not an explanation layer bolted on after the fact.
Auditable by construction
A full trail of each step’s work is produced as a side effect of how the agent runs — so you can verify exactly what it did and why. The architecture aligns with human-oversight expectations like those in the EU AI Act — staged review, audit trails, defined intervention points — with no separate logging system to build.
You stay in control
Each stage produces an output you can open, review, and correct before the next step runs. You steer the work at defined checkpoints instead of trusting a single opaque run end to end.
Right context, better answers
Each step receives only the information it needs, not one overloaded prompt. Scoped context means more reliable output, fewer hallucinations, and lower cost per run.
Yours to own — no lock-in
The whole agent workflow is plain text and standard files you own: version-controlled, diffable, reversible, and handed over clean. Copy it, move it, run it anywhere — no proprietary runtime to depend on.
Repeatable and predictable
Configure the workflow once, then run it again and again on new inputs with consistent behavior — the same pipeline, audited the same way, every time.
Common questions
Answers for builders and buyers
What kind of AI agents do you build?
We build agentic systems — software that uses tools, keeps memory, plans multi-step work, and acts under guardrails — for tasks like research, document processing, customer and citizen support, and workflow automation. Each agent runs on infrastructure you own and is scoped to exactly what its guardrails permit.
Can agents use our own documents and knowledge?
Yes. We build private retrieval (RAG) over your own documents, records, and institutional knowledge, turning them into a connected, searchable knowledge base. Answers are grounded in your sources with citations, and the data never leaves the infrastructure you control.
Which AI models can we use?
Any of them, or none. We are model-agnostic: self-host open-weight models on your own hardware, or connect a managed model your enterprise already uses. You can change models as the field moves, with no lock-in to one vendor.
Does our data stay private?
Yes. Agents and retrieval run on infrastructure you own — on-premises, at the edge, or in a sovereign cloud you control. Your data is never sold, mined, or used to train anyone else’s models, and every action is logged so you can audit exactly what happened.
How do you keep agents safe and accountable?
Guardrails scope what an agent can do, access is least-privilege by default, humans stay in the loop on consequential actions, and every step is logged for audit. The approach is backed by in-house ISO/IEC 27001 lead-audit capability and built to protect privacy by design.
Do you build software beyond AI agents?
Yes. We engineer production web platforms and data-driven applications to standards — accessible, fast, and tested — then hand them over clean with no lock-in. Whether or not AI is involved, the software you depend on is built by people accountable for it.
Put your knowledge to work — privately.
Tell us what you want an agent to do, or what knowledge you want it grounded in. We design, build, and run it — then hand it over yours.