AI & Smart Systems
RAG Development
Your knowledge, answering questions accurately.
RAG done well is an engineering discipline, not a vector-database demo. Chunking strategy, hybrid retrieval, reranking, citation grounding, and evaluation loops decide whether your assistant is trustworthy or embarrassing.
Sydova builds RAG systems over contracts, policies, product docs, tickets, and structured data — measured against golden question sets so accuracy is a number, not a feeling.
We ship the full stack: ingestion pipelines that stay in sync with your sources, retrieval tuned to your corpus, and a UI your team actually enjoys using.
What's included
RAG Development services we offer
Knowledge Assistants
Grounded Q&A over your corpus with citations, permissions, and feedback loops.
Ingestion Pipelines
Connectors, parsing, chunking, and incremental sync from your live sources.
Retrieval Tuning
Hybrid search, rerankers, and metadata filters benchmarked on your queries.
RAG Evaluation Harnesses
Golden datasets and automated grading so every change is measured.
How we work
A process built for certainty
- 1
Discovery
We map goals, users, constraints, and success metrics into a scoped roadmap with fixed milestones.
- 2
Design
UX flows and UI systems are prototyped, tested against real content, and signed off before build.
- 3
Build
Senior engineers ship in weekly sprints with code review, CI, and a demo environment you can click.
- 4
QA & Launch
Automated and manual QA, performance and accessibility audits, then a monitored, reversible launch.
- 5
Support
Post-launch SLAs, iteration sprints, and roadmap reviews keep the product improving.
Stack & models
Technologies and ways to engage
Fixed-scope project
Defined deliverables, milestone billing, and a warranty period.
- Signed scope & timeline
- Weekly demo cadence
- Best for bounded builds
Dedicated team
A stable pod on monthly capacity, steered by your priorities.
- Scales quarterly
- Roadmap-driven
- Best for products
Hourly / retainer
Flexible senior hours for audits, fixes, and advisory.
- 40-hour minimum
- Rolls over 1 month
- Best for ongoing needs
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Projects delivered
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Years in business
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Client retention
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5-star reviews
Proof
RAG Development in production
“Sydova treated accuracy like an engineering metric, not a marketing claim. That rigor is why schools trust the product.”
Priya Raman
Chief Product Officer, Lumina EdTech
FAQ
RAG Development — common questions
How accurate can RAG get on our documents?
On well-scoped corpora we routinely reach 90%+ answer accuracy on golden sets. The honest answer depends on your documents — which is why we baseline in week one.
Does our data leave our environment?
It doesn't have to. We deploy pipelines and vector stores inside your cloud, and can use region-pinned or self-hosted models.
Can it respect document permissions?
Yes — retrieval is filtered by the caller's entitlements, so users only ever see answers from documents they could open themselves.
What about hallucinations?
Grounded generation with citation checks, refusal thresholds when retrieval confidence is low, and eval suites that track hallucination rate as a first-class metric.
Related services
Where teams go next
AI Development
End-to-end AI product engineering — from model selection to production-grade shipping.
AI Chatbots & Conversational BI
Customer-facing assistants and natural-language analytics your teams can actually trust.
AI Agents & Workflow Automation
Agentic systems that execute multi-step business workflows with guardrails and audit trails.
Ready to start with rag development?
Tell us where you're headed — a senior specialist replies within one business day.