SYS-01 / Service
AI agents & LLM systems
We build AI agents that take real work off your team: triaging requests, drafting replies, reconciling data, preparing reports. They plug into the tools you already use, follow your rules, and hand decisions to a person when it matters.
01 / Capabilities
Agent design
We map the job, the tools it needs and where a human must sign off before anything is built.
Retrieval & memory
Search over your documents, tickets and databases so answers cite real sources.
Tool integrations
Agents call your CRM, helpdesk, spreadsheets and internal APIs through scoped, logged connectors.
Evaluation & guardrails
Test sets, output checks and policy rules run on every change, so quality is measured, not hoped for.
02 / How we deliver it
phase 01
Scope the job
One workflow, one owner, one success measure. We agree what "done" looks like.
phase 02
Prototype on real data
A working agent on a sample of your data within the first weeks.
phase 03
Harden
Guardrails, evals, logging, permissions and failure handling.
phase 04
Roll out & run
Gradual rollout with human review, then monitoring and monthly improvements.
03 / What changes
- Repetitive work moves from people to agents
- Every agent action is logged and reviewable
- People approve decisions; agents prepare them
- You own the code, prompts and evaluation data
04 / FAQ
Questions about AI agents & LLM systems.
What is the difference between an AI agent and a chatbot?
A chatbot answers questions. An agent completes work: it reads a request, plans the steps, calls your tools (CRM, helpdesk, spreadsheets, APIs) and returns a result. Ours prepare the work and wait for a person to approve anything that changes money, customers or records.
Which models do you build on?
Whichever fits the job and your data residency needs: Claude, GPT, Gemini or open-source models you host yourself. We design the system so the model can be swapped without rebuilding the integrations, prompts or evaluation sets around it.
How do you stop an agent from making things up?
Answers are grounded in your documents and systems and cite their sources. Every change is scored against an evaluation set before release and monitored after it. Anything uncertain is routed to a person rather than guessed.
How long does a first agent take?
A fixed-scope pilot on one workflow usually takes two to six weeks from kick-off to a working agent in your environment, depending on how many systems it touches. Hardening for production adds a few more weeks.
Where does our data go?
Wherever you decide. We can run the whole system inside your own cloud account and region, use model providers that do not train on your data, and keep access scoped to the task with every call logged.