Applied AI consulting
Custom Internal AI Assistants
Help staff find and use the information they are allowed to access, with source-linked answers and clear limits.
For teams switching between documents, wikis, and business tools to answer recurring questions or prepare first drafts.
Discuss your workflow
What the engagement produces
Knowledge and access assessment
Identify the source material, ownership, update frequency, and access rules. Define which questions the assistant should answer and which it should decline or escalate.
Assistant prototype and evaluation
Build a retrieval-based prototype on approved documents. Test source references, incomplete information, conflicting documents, and attempts to retrieve material outside a user’s permissions.
A practical integration plan
Scope a connection to Slack, Teams, an intranet, or another existing interface where its APIs and access rules permit. Include feedback handling, content updates, and operating documentation.
How we work with your team
- Subject-matter owners provide representative questions and approved answers. Technical owners identify identity and access constraints.
- We test retrieval and answer quality before expanding the source set. Your reviewers assess whether citations support the answer and whether escalation is useful.
- We agree on deployment, monitoring, user guidance, and ongoing content ownership before wider use.
Scope and responsibilities
An assistant can make mistakes. It is not a substitute for professional judgment, and access to a chat interface must not grant access to otherwise restricted records. Model providers, retention, hosting, and connector permissions require explicit scope decisions. A prototype is not proof of production readiness.
Customer support automation
Support teams can apply the same approach to ticket categorization, knowledge retrieval, and draft replies. Start with suggestions reviewed by staff, a maintained knowledge base, and a clear path to a human. Any customer-facing answer or automated send needs separate evaluation and an agreed release boundary. We measure answer usefulness and escalation quality rather than assuming that fewer tickets means better support.
Illustrative use case: an internal policy assistant
A staff member asks which purchasing approval is needed. The assistant locates the relevant policy, links to its source, and directs ambiguous cases to the policy owner. This is an example of a possible workflow, not a client result.
See how we scope and validate a pilot →Prepare for the conversation
Bring the process you want to improve, the tools involved, and examples you are allowed to share. Leave confidential records out of the initial inquiry.
Compare building and buying an AI tool →Start with one useful problem
Tell us what your team needs to do, where the current process breaks down, and who will own the result.
Discuss your workflow