AI Development
RAG Development Services
We build Retrieval-Augmented Generation (RAG) systems that answer from your documents—not guesses. Expect clean ingestion, tuned retrieval, citations, and an evaluation loop that improves accuracy over time. Delivery aligned to United Kingdom teams (GBP).
Overview
What this service is
RAG combines search with LLM responses: it retrieves relevant source passages and then generates an answer grounded in those sources.
We engineer the full stack—connectors, chunking, embeddings, hybrid search, reranking, and access control—so retrieval is reliable in real conditions.
You get monitoring and evaluation tests so your team can iterate without breaking quality as content and prompts evolve.
Start Small
Start small in 7 days
Three pilot-friendly options that reduce risk and ship value fast. Choose one, share access, and we deliver a production-ready baseline.
Standard
AI delivery standard
Quality and safety practices we ship with AI builds so the system stays measurable, maintainable, and production-ready.
Logging + tracing
Conversation and tool traces with request IDs, error visibility, and debug-friendly runbooks.
Guardrails + safety
Tool allowlists, PII-safe patterns, refusal behavior, and escalation routes for edge cases.
Evals + regression tests
Golden queries, scorecards, and regression checks so quality improves over time instead of drifting.
Cost + latency controls
Caching, prompt discipline, retrieval tuning, and routing so your app stays fast and predictable at scale.
Documentation + handoff
Architecture notes, environment setup, and next-step roadmap so your team can iterate safely after launch.
Security-first integration
Secrets isolation, role-based access, audit-friendly actions, and minimal data retention by design.
Benefits
What you get
Lower hallucinations with source-grounded answers
Better retrieval quality via hybrid search + reranking
Safer UX with citations and low-confidence fallbacks
Freshness via incremental indexing pipelines
Permission-aware access for internal/tenant data
Measurable accuracy via eval sets and regression tests
Features
What we deliver
Ingestion pipelines
Connect PDFs, docs, wikis, websites, help centers, tickets, and databases with clean normalization and metadata.
Chunking + metadata strategy
Right-sized chunks with stable IDs, versioning, and filters so retrieval stays accurate as content changes.
Vector database setup
Schema, indexing, backups, and performance tuning for Pinecone, Qdrant, Weaviate, or pgvector based on your constraints.
Hybrid search + reranking
Combine keyword + semantic retrieval and rerank results to improve precision for exact terms, error codes, and product names.
Citations + excerpt UX
Answers include sources and highlighted passages so users can verify and drill into the original content.
Evaluation + monitoring
Golden queries, regression checks, retrieval metrics, and dashboards so quality improves continuously after launch.
Process
How we work
Discovery
Sources, permissions, query goals, and evaluation criteria.
Ingestion
Connectors, parsing, normalization, and metadata.
Retrieval
Embeddings, vector DB, hybrid search, and reranking.
Answer UX
Citations, excerpt UI, and fallback behavior.
Evals + launch
Regression tests, monitoring, and rollout plan.
Tech Stack
Technologies we use
Core
Tools
Services
Use Cases
Who this is for
Support knowledge base assistant
Answer tickets from docs and policies with citations and escalation when evidence is weak.
Internal SOP / runbook search
Search across internal procedures and knowledge while respecting access rules and audit needs.
Product docs + developer assistant
Explain APIs, error codes, and configuration with precise citations and up-to-date versioning.
Compliance / policy Q&A
Ground answers in official policy docs, track sources, and provide safe “I can’t confirm” fallbacks.
Sales enablement assistant
Find the right case studies, pricing rules, and product positioning fast—without misinformation.
AI Case Examples
Micro case studies (anonymous)
A few safe examples of outcomes we build for real operations—no client names, just results.
Secure Mobile Solution in Australian Defence Ecosystem
Problem: Secure data workflows were required in a regulated environment with strict access controls.
Solution: Hardened architecture with strict auth, encrypted storage, and audit-friendly engineering patterns.
Outcome: Deployed securely within a regulated ecosystem with clear handoff and operational guidance.
AI Knowledge Base Across 2,000+ Pages
Problem: Teams needed fast answers across long PDFs, but search was slow and results were inconsistent.
Solution: RAG with hybrid retrieval and reranking, plus grounded answers and safer fallback behavior.
Outcome: Reliable answers with <10s response times and measurable improvements on real queries.
Ops Automation with AI + n8n
Problem: Manual approvals and CRM syncing created delays and data inconsistencies across tools.
Solution: Event-driven automation with validation gates and AI-assisted classification where it improved routing.
Outcome: Reduced manual workload significantly with more reliable workflows and operator visibility.
Explore
Related solutions & technologies
Useful next pages if you’re planning an AI pilot or scaling this into a larger product.
Related solutions
FAQ
Frequently asked questions
It depends on your constraints. Pinecone is managed and operationally simple, Qdrant/Weaviate are great for self-hosting, and pgvector is strong if you’re already on Postgres. We recommend based on scale, cost, and infra preferences.
Yes. We can implement per-user or per-tenant filtering, source-level permissions, and auth integration so retrieval respects access rules.
We improve retrieval quality, require citations/excerpts, add low-confidence fallbacks, and test with evaluation queries that reflect real user needs.
We build incremental indexing and scheduled refresh pipelines so new or updated docs are reflected without full re-ingestion.
Yes. Hybrid retrieval and reranking are often the biggest accuracy unlocks for production RAG systems.
A first production RAG system often ships in 3–6 weeks depending on sources, permissions, and UX complexity.
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Regional
Delivery considerations for your region
Compliance & Data (UK/EU)
For UK teams, we default to GDPR-first thinking: data minimisation, purpose-limited storage, and clear access boundaries.
We can work under a DPA (template available on request) and implement practical retention/deletion flows when needed.
- GDPR-first patterns (minimise, restrict, document)
- DPA template available on request
- Retention/deletion and export flows where required
- Least-privilege access and secure session handling
- PII-safe logging + secure-by-default configuration
- NDA available for early-stage discussions
Timezone & Collaboration (UK/EU)
We align to UK time and EU overlap (GMT/BST with CET-friendly windows) for fast feedback cycles.
We keep the process lightweight: async updates, clear priorities, and written decisions to avoid ambiguity.
- UK/EU overlap with GMT/BST windows
- Async-first delivery with documented scope
- Weekly milestones and structured demos
- Clear escalation path for blockers
- Tight change control with clear sign-offs
Engagement & Procurement (UK)
We support typical UK procurement flows with clear scopes, change control, and invoice cadence.
If you prefer a discovery-first engagement, we can run a short paid discovery to lock requirements before build.
- GBP-based engagements and invoicing options
- Discovery-first option to reduce delivery risk
- Milestone-based billing when appropriate
- Transparent change control and sign-offs
- Vendor onboarding pack on request
Security & Quality (UK/EU)
We build for reliability and maintainability: clean PRs, tight review loops, and test coverage that matches risk.
Performance budgets and release checklists keep launches predictable—especially when multiple stakeholders review changes.
- CI-friendly testing: unit + integration + smoke tests
- Performance budgets + bundle checks (Core Web Vitals-minded)
- Structured release notes and rollback-safe deployments
- Security checklist for auth, roles, and data flows
- Observability hooks (logs + error tracking) ready for production
Want help with RAG development?
Share your requirements for United Kingdom delivery. GBP-based engagements.
Reply within 2 hours. No-pressure consultation.