AI
Approved internal knowledge becomes easier to find and use in the right context.
Salytiq builds a bounded assistant with approved sources, traceable references and clear answer limits.
Salytiq builds a bounded assistant with approved sources, traceable references and clear answer limits.
From intake to outcome
- 01Bound user questions, sources and permissions
- 02Assess document quality and freshness
- 03Implement retrieval, context and response logic
- 04Test references, unknowns and feedback path
Business outcomes
- Faster knowledge access
- Traceable sources
- Fewer recurring internal questions
Typical deliverables
- Source and permissions concept
- Retrieval and context pipeline
- Focused assistant interface
- Evaluation cases, limitations and operating guide
When the solution fits
- Teams repeatedly search for the same internal information
- Documentation is extensive but basically maintained
- Answers should cite sources and expose uncertainty
Scope boundaries and prerequisites
Clear boundaries
- Poor or conflicting sources do not become reliable through AI
- Permissions, privacy and hallucination risk determine scope
Required foundations
- Approved accessible knowledge sources
- Owners for content, permissions and evaluation
How an engagement can work
- 01
01 Understand
Capture the workflow, effort, systems and visible pain.
- 02
02 Prioritise
Align impact, feasibility and economic value.
- 03
03 Implement
Build, test and clearly hand over one bounded workflow.
- 04
04 Operate
Monitor and improve within an agreed scope.
Frequently asked questions
What does Internal AI Assistants include?
Salytiq builds a bounded assistant with approved sources, traceable references and clear answer limits. Typical deliverables include: Source and permissions concept; Retrieval and context pipeline; Focused assistant interface; Evaluation cases, limitations and operating guide.
What information is needed to get started?
A robust initial scope requires: Approved accessible knowledge sources; Owners for content, permissions and evaluation.
When is this solution a good fit?
A useful starting point is especially likely when: Teams repeatedly search for the same internal information; Documentation is extensive but basically maintained; Answers should cite sources and expose uncertainty.
Which boundaries are clarified before implementation?
Transparent scope boundaries are part of the work: Poor or conflicting sources do not become reliable through AI; Permissions, privacy and hallucination risk determine scope.
How can an engagement begin?
We first understand the workflow and prioritise one clearly bounded step. Where the starting point remains unclear, an Automation Audit can prepare the right implementation.
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