Service

Generative AI, RAG and AI Assistants

Build grounded assistants and knowledge workflows with permission-aware retrieval, evaluation, and human review.

QALIX / delivery systemOperational

Capability systemGenAI & RAG

Product Data Platform

Delivery signalWorking increment

System state Ready for evidence

Quality · security · operations

Who this is for

For organizations that need useful AI over trusted content without exposing data or relying on unmeasured demo behavior.

Outcomes

Grounded responses
Permission-aware knowledge access
Clear refusal and escalation paths
Continuous quality evidence

Capabilities

Retrieval architecture
Assistant experience design
Evaluation harnesses
Guardrails and human review

Approach

Map the operating reality, users, constraints, and success measures
Make the riskiest product and technical decisions visible early
Ship working vertical increments with quality and observability
Use real adoption and operational evidence to guide evolution

Deliverables

Knowledge-source audit
RAG prototype
Evaluation set
Integrated assistant workflow

Selected technologies

OpenAI API
Vector search
PostgreSQL
Python
TypeScript

Related industries

professional services
education and learning technology
media and content platforms

Contextual next step

Share the workflow, platform, or product challenge you are trying to resolve.

Discuss this service

Service FAQs

Can QALIX work with an existing product or engineering team?

Yes. QALIX can lead a defined workstream, add senior specialists, or form a focused multidisciplinary squad with clear delivery ownership.

What does a first engagement usually produce?

The first phase makes scope, risks, architecture, success measures, and the smallest credible release explicit before delivery expands.

How are delivery risks handled?

QALIX uses working increments, visible acceptance criteria, automated checks, operational evidence, and explicit decisions instead of hiding risk in status reporting.