AI development
Custom AI development for business operations
Not a demo, and not a chatbot bolted onto a website. Systems that do a job inside an operation that already runs — built in your accounts, documented so they outlast us.
Scope
What we build
Four kinds of system. The audit decides which one your problem actually needs.
- Retrieval — answers grounded in your own documents, tickets and history, with the source attached, rather than a general model's guesswork.
- Generation — pipelines that produce content, quotes or analyses at volumes no team could staff, with quality checks before anything ships.
- Operations — the daily reporting, reconciliation and collation that consumes someone's morning, running on a schedule instead.
- Outbound — acquisition engines that source accounts against an ICP, enrich them, write per account and classify every reply.
Evidence
Where this has been done
Built at Koenig Solutions
Prior professional experience. Our founder built these systems as an employee at Koenig Solutions, who own them.
Retrieval and generation over a course library
A retrieval system across a library of 8,000+ courses, and a generation pipeline that produced 350,000+ practice questions grounded in that syllabus rather than invented, each quality-checked before publication.
Built and run by Ergara
A working tool, in public
The Networking Contact Finder is ours — built, hosted and running on this domain with no sign-up and nothing to install. It is the quickest way to see how we build before talking to us.
A GPS-verified checklist system in daily use
Built for Super Donuts and in pilot at one of the chain's six outlets since May 2026, with the opening checklist live. A manager can only start once GPS confirms they are in the store, and head office approves a section or sends it back.
How engagements work
One workflow is mapped in the free AI Ops Audit, then ranked against everything else worth building. Scope and price are fixed before anything starts, half is due to begin, and the balance only after fourteen days of correct running.
30 minutes, no pitch, and a ranked list of what to build first.
What you own
What you are actually buying
You'll own it
Built in your accounts, on your credentials, documented. If you stop working with us, nothing stops working.
No handoffs
The people who map your workflow are the people who deliver the system. No account manager, nothing thrown over a wall to a team that never spoke to you.
Questions
About ai development
What does “grounded in your data” actually mean?
The system retrieves from your own material and answers from what it found, with the source attached. Where the answer is not in your material it says so, rather than producing a confident guess. That is the difference between something you can put in front of staff and something that demos well.
Whose accounts and API keys does this run on?
Yours, throughout. The model provider, the database and the hosting are billed to you directly in your own accounts, and the audit tells you what that should cost before you commit. You can revoke our access at any point without anything stopping.
What happens when a model is deprecated?
We put the model behind an interface, so replacing one is not a rebuild of the system around it. It is not frictionless either, and we would rather say so: a different model usually needs configuration changes, prompt changes and a round of evaluation against your own examples before we would put it live. Where a monthly maintenance engagement is running, that migration is covered by it. Without one, it is scoped as a piece of work like anything else.
Find out what you shouldn't be doing.
30 minutes, no pitch, and a written plan you keep either way.
Get your free AI Ops Audit