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Internal policy and manual assistant
The problem Scattered manual versions lead to inconsistent answers
Question search with cited sources and document version
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Custom AI solutions for business
Design and build AI solutions around real company work, from data and marketing to sales, customer service and internal operations.
Discuss your project ↗
When does this service help?
Teams use different data, tools and processes, so an off-the-shelf AI tool may not fit. We turn operational problems into testable use cases and connect solutions to existing work.
Illustrative expected outcomes
Before
Staff spend time searching approved product specs across multiple folders to answer questions.
Expected After
An AI assistant searches approved sources and drafts answers for staff review.
Business Value
Staff can respond faster and handle more inquiries in less time.
How to Measure
- Information search time
- Answer accuracy after review
- Repeated requests
Industry Example
Example: A wholesale equipment company needing to answer product specification questions.
What we can work on
- Internal AI assistants and work support
- Company knowledge search and answers
- Document classification, summaries and processing
- AI for marketing, sales and customer service
- Integration with existing software and workflows
- Quality checks, data access and human handoff
How we approach the work
We review authorized workflows and data, select a focused first use case, build and test a prototype in real work, then improve it with clear human review points.
Define AI tasks and human review points
Consider custom AI when answers need company knowledge or specific workflow integrations. Evaluate existing tools first when they already meet the requirements.
Deliverables to agree before starting
Data boundaries, test examples, a scoped prototype, answer evaluation criteria and human handoff when information is insufficient.
What to prepare
Prepare representative questions, approved documents, integration requirements and a subject-matter reviewer.
Scope and limitations
AI can make mistakes and needs evaluation. Model/API usage, data migration and ongoing support require explicit agreement.
Discuss your requirements →See what the work can look like
Three enduring business problems, shown through the work designed to solve them.
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Document extraction and review
The problem Teams re-enter document data and miss checks
Extracted fields, confidence and human review queue
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Product-spec answer assistant
The problem Product specs in many sources slow replies and risk model mix-ups
Question, product model, sources and draft answer
View full-size visualBefore we begin
When does a custom AI solution make sense?
A custom solution may help when the task needs internal data, role-based access or steps that existing tools cannot support. We review the available options first and identify what actually needs development; a full rebuild is not always necessary.
What data is needed for an AI assistant using company documents?
Start with the questions it should answer, examples of documents you are allowed to use and the person responsible for their accuracy. Redact confidential details from initial samples. We then agree on user permissions, reference sources and document updates.
How do we assess whether the AI is ready to use?
We agree on test questions and acceptance criteria before development. Tests cover supported answers, out-of-scope requests and missing information, with defined points for human review or handoff. One successful demonstration does not establish readiness.
Does an AI project quote include model usage and ongoing support?
The proposal separates development, integrations, model or API usage, hosting and support, and states which are included. We estimate these after reviewing workload, existing systems and data constraints rather than quoting a universal package.
EXPLORE MORE
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Help teams answer questions, qualify enquiries, follow up and hand important cases to people.
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