What we solve
For teams that spend time searching documents, repeating answers, and gathering information from several systems. A chat interface alone is not enough: the assistant must understand company context and avoid presenting confident guesses as facts.
What you get
The assistant answers from permitted data, cites sources, respects the user’s role, and hands complex cases to a person. Quality is measured against a prepared set of real questions.
What is included
- Research into use cases and knowledge sources
- Search, RAG, and access-control architecture
- An interface or integration with a working channel
- A test-question set and quality metrics
- Logging, feedback, and a process for updating knowledge
How we work
- Choose a limited use case with measurable value.
- Prepare the data and a reference test set.
- Build a prototype and assess answer quality.
- Launch a pilot, review errors, and refine the rules.
Optional additions
- Integration with CRM, helpdesk, or a portal
- Support for multiple languages
- Actions through tools and APIs
- A quality and usage dashboard
Important considerations
Data access, freshness, and user permissions must be designed before launch. The assistant should not make critical decisions without a person’s approval.