AI, Data & Intelligence
Custom AI Assistants
Purpose-built AI assistants for a specific role or team, such as underwriters, relationship managers or field engineers, that combine your data, tools and procedures in ways off-the-shelf assistants cannot.
Capability overview
What custom ai assistants involves
General workplace assistants know a user's email and files, but not how an underwriter assesses a proposal or how a field engineer diagnoses a pump. Custom AI assistants are built around one role's actual work: the systems they check, the rules they apply, the documents they produce and the decisions they escalate.
An underwriting assistant might pull applicant data from the policy system, summarise medical reports, flag guideline exceptions and draft the decision note. A field service assistant might retrieve the asset's maintenance history, suggest diagnostic steps from manuals and create the work order. The assistant supports decisions; the professional still makes them.
What is included
What a custom assistant combines
Role workflow mapping
The sequence of checks, lookups and outputs in the role captured from observation, not only from written procedures.
System tools
Read and limited write access to the specific applications the role uses, exposed as safe, auditable tools.
Domain guidance
Manuals, guidelines, rate tables and precedent cases made searchable and applied consistently to each case.
Structured outputs
Drafts of the notes, reports, emails or forms the role produces, in the exact format reviewers expect.
Mobile and offline considerations
Interfaces suited to where the work happens, including mobile use on site with limited connectivity.
How we work
How we deliver custom ai assistants
Role shadowing
Time spent with experienced staff to understand shortcuts, judgement calls and common mistakes.
Task prioritisation
The steps that consume the most time or cause the most rework chosen for the first release.
Assistant build
Tools, knowledge sources and interface built and tested on historical cases.
Expert calibration
Senior staff review assistant suggestions on real cases and refine guidance until they trust its output.
Team rollout
Released to the wider team with training, feedback capture and measurement of handling time and quality.
Related capabilities
Related capabilities in Generative AI & LLM Engineering
AI Copilots
AI copilots embedded inside your own software product or internal platform, helping your users complete tasks in context, with features designed, priced and governed as part of the product.
LLM-Powered Agents
LLM-Powered Agents within our generative ai & llm engineering services, scoped after a short discovery conversation.
Prompt Engineering
Systematic design, testing and versioning of the instructions that drive language model behaviour, so outputs are accurate, consistently formatted and stable when models or inputs change.
LLM Integration
Adding large language model capabilities to existing applications through provider APIs, handling streaming, structured output, rate limits, retries, data redaction and switching between providers.
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Where this applies
Healthcare & Life Sciences
Technology systems for regulated environments where privacy, auditability and continuity…
Manufacturing & Industrial
Connected operations, asset, field, supply chain and industrial platforms for complex operating…
Banking, Financial Services & Insurance
Technology systems for regulated environments where privacy, auditability and continuity…
E-Commerce
Digital platforms for customer experience, operations, commerce, content, marketing and service…
Questions & answers
Questions about Custom AI Assistants
Cannot find what you need? Our team responds to technical and commercial questions within one business day.
Ask a questionAn assistant works alongside a person who directs it and makes the decisions. An agent completes tasks on its own within set limits. Custom assistants often include a few agent-like actions, each confirmed by the user.
Yes, where requirements fit its connectors and controls. Copilot Studio suits Microsoft-centric organisations with moderate complexity, while fully custom builds suit complex integrations or strict hosting requirements.
A first release covering the highest-value tasks for one role typically takes eight to twelve weeks, including calibration with experienced staff.
The first release is a fixed-price project defined after role shadowing. Further capabilities are added in fixed-scope phases, with hosting and support billed monthly.
Next step
Discuss custom ai assistants with Acmez
Share what you need to change, build, integrate or support. We will map the practical next step.