/ AI support
AI automation systems need active maintenance after launch. We support RAG workflows, assistants, prompts, model choices and evaluations so the system keeps improving as usage, data and model behaviour change.
AI products are not static. Models change, costs move, prompts degrade, new edge cases appear and users quickly reveal where the workflow needs sharper context or better guardrails.
Our AI automation retainers give businesses a technical partner for ongoing tuning, prompt engineering, retrieval quality, monitoring, model updates and practical improvements that keep AI systems useful in production.
Ongoing refinement of system prompts, tool instructions and response formats based on real usage and failure cases.
Chunking, retrieval, ranking, metadata, source grounding and answer quality improvements for knowledge systems.
Evaluation and migration support as newer, faster or more cost-effective models become appropriate.
Test sets, review workflows and scoring criteria to measure whether the AI is actually improving.
Usage, latency and model spend reviewed so automation remains commercially sensible as volume grows.
Practical changes to automations, handoffs and fallback paths as teams discover how they want to work with AI.
We review the current AI workflow, data sources, prompts, model choices, user journeys and known failure cases.
We define the quality signals that matter: answer accuracy, source grounding, completion rate, latency, cost and escalation rate.
We improve prompts, retrieval, context, tools and model settings in controlled iterations.
We keep the system aligned with new models, new business data and the way users actually behave.
Because prompts, retrieval quality, model behaviour, user needs and costs all change. Production AI needs monitoring and tuning like any other business-critical system.
Often, yes. We start by reviewing the architecture, data sources, prompts and evaluation approach before taking responsibility for improvements.
Yes. Retrieval quality, source grounding and answer evaluation are central parts of the support we provide.
In many cases, yes. We review model selection, prompt length, retrieval context, caching and workflow design to reduce unnecessary spend.
Tell us what needs to change. We will come back with a route, a timeline and a number.
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