AI Agent Consulting & Implementation
Auremere helps companies design, build and operate AI agents that take on real operational work — from the first assessment through running in production.
What we do
Most AI programmes stall between a promising prototype and something the business actually runs on. We work on that gap — the design decisions, the engineering, and the operations that make an agent dependable.
We assess where agents genuinely pay off in your operation, define the use cases worth building, and set the architecture and guardrails before anyone writes code.
We build the agents themselves — tool use, retrieval, orchestration, evaluation and the integration work that connects them to your existing systems.
We help teams run agents after launch: monitoring, evaluation, cost control and the iteration cycle that keeps quality from drifting.
How we work
Every engagement starts with a concrete outcome rather than a platform choice. We work in four stages, and you can stop after any of them.
Understand the process, the data and the constraints. Decide whether an agent is the right answer at all.
Define scope, architecture, evaluation criteria and success metrics — including what "good enough" means.
Implement against real data, with evaluation running from the first sprint rather than bolted on at the end.
Ship to production, monitor it, and hand over a system your own team can extend.
Where we help
Agents that triage, resolve and escalate support and service requests, with humans kept in the loop where it matters.
Research, analysis and document-heavy processes where the bottleneck is reading, summarising and producing rather than deciding.
Turning expertise into repeatable, instrumented workflows that a team can run at volume without losing quality.
Helping product teams add agent capabilities to their own software — architecture, tooling and evaluation.
A short description of the process and the constraint is enough to start.