AI Development
RAG Development Services
We build Retrieval-Augmented Generation systems that answer from your content, not guesses. Expect clean ingestion, tuned retrieval, citations, and an architecture built for ongoing updates.
Overview
What this service is
We convert your sources—PDFs, wikis, help centers, tickets, and databases—into a searchable knowledge layer with metadata and versioning.
Retrieval is designed for trust: citations/excerpts in responses, permission-aware access, and fallback behavior when the system is uncertain.
We tune chunking, filters, hybrid search, and reranking against a test set so retrieval quality improves predictably as your content grows.
Benefits
What you get
Higher accuracy for customer and internal answers
RAG pulls relevant context so responses stay grounded in real, current content.
Trust-building citations
Users can verify sources and follow links to the exact excerpt behind an answer.
Faster onboarding and support resolution
Teams find answers quickly across large doc sets, reducing repetitive manual searching.
Permission-aware knowledge access
Access rules and role boundaries can be respected when needed for internal systems.
Measurable, testable improvements
Eval sets and regression checks make retrieval tuning safer and more repeatable.
Features
What we deliver
Ingestion pipeline
Parsers, normalization, and update workflows for PDFs, docs, web content, and structured sources.
Chunking + metadata strategy
Chunking tuned to your domain plus metadata that supports filters and access control.
Vector DB setup
Pinecone/Qdrant/Weaviate/pgvector schemas, indexes, and performance-ready configuration.
Hybrid search + reranking
Combine keyword + vector retrieval and rerank results for better relevance and fewer misses.
Citations and excerpts in answers
Answer formatting designed for trust, with consistent source attribution and links.
Monitoring + eval loop
Quality checks, retrieval diagnostics, and feedback signals to keep performance stable over time.
Process
How we work
Source audit
We review your content sources, access rules, and target queries to define the retrieval plan.
Ingestion build
We implement parsing, chunking, metadata, and update workflows for your chosen sources.
Retrieval + generation
We wire hybrid retrieval, reranking, prompting, and response formatting with citations.
Evaluation
We create a query set and iterate on retrieval settings to hit accuracy and latency targets.
Launch
We deploy, monitor, and document how to maintain and evolve the knowledge base over time.
Tech Stack
Technologies we use
Core
Tools
Use Cases
Who this is for
Support knowledge assistant
Answer from docs and help center content with citations and clean escalation to humans.
Internal policy and SOP search
Find answers across handbooks, runbooks, and internal docs with role-aware access controls.
Product documentation copilot
Help users and engineers locate implementation details, examples, and API references quickly.
Sales enablement assistant
Answer product questions from approved collateral and generate structured summaries for follow-ups.
Document-heavy research workflows
Search across large PDF libraries with citations and versioning for consistent results.
FAQ
Frequently asked questions
PDFs, docs, web pages, help centers, wikis, tickets, and structured sources like databases or APIs. We tailor parsing and chunking per format.
Yes. We include citations and excerpts wherever possible so users can verify the source behind an answer.
Yes. We can implement permission-aware retrieval and filtering aligned to your RBAC model when your access rules are available.
We build update jobs and re-indexing workflows so new or changed documents are reflected reliably without manual effort.
Yes. We can embed RAG into your product via an API, a widget, or an internal tool experience depending on your stack.
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Regional
Delivery considerations for your region
Compliance & Data (EU)
For Germany/EU delivery, we keep GDPR-first patterns: data minimisation, purpose-limited storage, and explicit access boundaries.
We can work under a DPA (template available on request) and implement pragmatic retention/deletion flows when needed.
- GDPR-first architecture patterns (generic, no legal claims)
- DPA template available on request
- Retention/deletion and export flows where required
- Least-privilege access and safe logging defaults
- Documented data flows and access boundaries
Timezone & Collaboration (EU)
We align to EU working hours with CET-friendly collaboration windows and async progress updates.
We keep delivery predictable: weekly milestones, documented decisions, and clear scope control.
- EU overlap with CET-friendly windows
- Async-first delivery with written decisions
- Weekly milestone demos and progress checkpoints
- Clear change control to avoid surprises
- Escalation path for blockers and risks
Engagement & Procurement (EU)
We support procurement-friendly engagements with clear scopes, milestone plans, and documentation that stakeholders can review.
For EU teams, we can structure invoices and milestones for EUR-based engagements where appropriate.
- EUR-based engagements and invoicing options
- Discovery-first option to reduce delivery risk
- Milestone-based billing and scope sign-offs
- Vendor onboarding documentation on request
- Transparent change control and approvals
Security & Quality (EU)
We prioritise reliability: reviewable PRs, predictable releases, and tests that protect critical paths.
Performance budgets and clear release discipline keep the product stable as it grows.
- CI-friendly testing: unit + integration + smoke tests
- Performance budgets + bundle checks
- Release checklist + rollback-safe deployments
- Security checklist for auth and sensitive data flows
- Observability hooks (logs + error tracking) ready for production
Need answers grounded in your own data?
Send sample docs + target workflows and we’ll recommend the right RAG stack, timeline, and rollout plan.
Citations + measurable quality checks included.