RAG Development: AI That Answers From Your Own Data
We build retrieval-augmented generation (RAG) systems that ground LLM answers in your documents and databases, with the retrieval quality, citations, permissions and evaluation needed to trust them in production.
What we build
- Enterprise knowledge assistants Answers from policies, wikis and manuals
- Document Q&A Ask questions across PDFs, contracts and reports
- Support knowledge bots Faster, consistent answers for customers and agents
- Semantic and hybrid search Find content by meaning, not just keywords
- Ingestion and indexing pipelines Parse, chunk, embed and keep content fresh
- RAG evaluation Measure retrieval and answer quality
- Grounded Answers with citations from your data
- 17+ Years of engineering experience
- ISO 27001 Certified information security
- ISO 9001 Certified quality management
- India + USA Global delivery
What Do You Want Your RAG System to Do?
Pick the one closest to your goal and see how we would approach it.
Make Internal Knowledge Searchable
Let employees ask questions and get answers from policies, wikis and manuals.
Speed Up Customer Support
Give agents and customers accurate, cited answers from your help content.
Query Contracts and Reports
Ask questions across long documents and see exactly where the answer came from.
Respect Document Permissions
Make sure people only get answers from content they are allowed to see.
Fix Poor RAG Answers
Diagnose weak retrieval, bad chunking and hallucinations in an existing system.
Check If RAG Is the Right Fit
Review your content and questions, then get a phased plan.
Not sure if RAG is right for you?
Tell us what questions you want answered and our AI experts will suggest the right approach.
RAG Development Services We Offer
Production-grade retrieval-augmented applications over your private documents and databases
Enterprise Knowledge Assistants
Assistants that answer employee questions from internal documents, with citations.
- Policies and wikis
- Citations
- SSO
Document Q&A
Question answering over PDFs, contracts, reports and long-form content.
- PDF parsing
- OCR
- Long documents
Customer Support Knowledge Bots
RAG assistants for help centers and support teams, with escalation to humans.
- Help content
- Escalation
- Multilingual
Semantic and Hybrid Search
Search that combines keyword and vector retrieval with reranking.
- Vector search
- Hybrid search
- Reranking
RAG Pipeline Engineering
Ingestion, chunking, embedding and indexing pipelines that keep content current.
- Chunking
- Embeddings
- Re-indexing
Agentic and Multi-Source RAG
Systems that plan multi-step retrieval across documents, databases and APIs.
- Multi-hop
- SQL + docs
- Tool use
RAG Evaluation and Tuning
Retrieval and answer quality metrics, test sets and continuous improvement.
- Test sets
- Metrics
- Tuning
Secure and Permission-Aware RAG
Access control at retrieval time so users only see what they are allowed to see.
- Access control
- PII handling
- Audit logs
Looking for something else? Explore our full AI development services, AI Agent Development, Generative AI Development, LLM Development.
Built for Real Business Problems
Real engagements, real outcomes. Every result below comes from a documented client case study.
Accessible Articulate Storyline 360 Courses for a Corporate Training Provider
A US-based corporate training provider needed its Articulate Storyline 360 compliance courses to work for learners using screen readers, keyboards and captions. D2i Technology audited and remediated the course library to WCAG 2.1 AA and Section 508.
Read Full Case Study of Accessible Articulate Storyline 360 Courses for a Corporate Training ProviderBuilding a CA Services Marketplace for MyTaxProf
MyTaxProf set out to connect clients with Chartered Accountant (CA) firms through one digital platform. D2i Technology built a custom, multi-role CA services marketplace covering service discovery, firm onboarding and verification, and structured service requests.
Read Full Case Study of Building a CA Services Marketplace for MyTaxProfWebsite Redesign at New Life Agency
New Life Agency needed a modern, professional website that truly reflected their reputation. D2i Technology redesigned their digital presence from the ground up — delivering a faster, more intuitive, and fully responsive experience built to support their continued growth.
Read Full Case Study of Website Redesign at New Life AgencyWhy Businesses Choose RAG
RAG lets an LLM answer from your current, private knowledge instead of relying only on what it learned in training.
Use your own data
Answers grounded in your documents, not just public training data.
Always up to date
Update the index instead of retraining a model.
Cited answers
Responses point to the source so people can verify them.
Control and privacy
Your content stays in your environment, with permissions enforced.
Lower cost than retraining
Often cheaper and faster than fine-tuning a model on your content.
RAG, Fine-Tuning or Something Else?
There is no single right answer. Here is how we would think about it.
| If you need... | Consider... |
|---|---|
| Answers from private, changing documents | Standard RAG |
| Questions across databases and documents | Hybrid RAG with text-to-SQL |
| Complex questions needing several lookups | Agentic RAG |
| Finding documents by meaning | Semantic or hybrid search |
| A particular tone, format or domain behavior | RAG plus fine-tuning |
| To check feasibility before a big investment | A scoped proof of concept |
From Documents to Trusted Answers
A proven 6-stage process from first idea to a system running in production
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Step 01
Discover
Define the questions, review your content and set quality targets.
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Step 02
Ingest and Index
Connect sources, parse, chunk and embed your content.
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Step 03
Retrieve and Rank
Tune search, hybrid retrieval and reranking for relevant context.
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Step 04
Generate
Design prompts, citations and guardrails around the retrieved context.
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Step 05
Evaluate
Measure retrieval and answer quality on a real question set.
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Step 06
Deploy and Monitor
Integrate, track quality and cost, and keep the index fresh.
What Happens After You Contact D2i?
No big commitment up front. Here is what the first few weeks look like.
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Step 1: 30-minute discovery call
We listen to the problem you want to solve.
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Step 2: Data and feasibility review
We check what data and systems you have and what is realistic.
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Step 3: Solution proposal
Approach, team and estimate in writing.
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Step 4: Delivery plan
Milestones, evaluation criteria and who does what.
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Step 5: Start building
Your team is onboarded and sprint one begins.
We Don't Stop at a Working Demo
Your RAG system ships ready for real questions, real documents and real scrutiny.
Accurate
Retrieval and answer quality measured on a real question set.
Secure
Permission-aware retrieval, encryption and ISO 27001 certified processes.
Verifiable
Citations let users check every answer against its source.
Scalable
Indexing and serving designed around your content volume and traffic.
Monitored
Quality, latency, cost and failed-query tracking in production.
Maintainable
Re-indexing, documentation and SLA-backed support after launch.
Security and Trust Built Into Your RAG System
Your documents are sensitive. We protect them, enforce permissions and test answer quality at every stage.
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Data
NDAs before any data is shared, plus redaction where required.
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Index
Encrypted storage and strict access to vector stores and sources.
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Retrieve
Permissions enforced at retrieval time, so users see only what they should.
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Evaluate
Accuracy, grounding and hallucination testing before release.
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Monitor
Failed queries, drift and content freshness tracked after go-live.
- ISO 27001
- NDAs
- Permission-aware retrieval
- End-to-end encryption
- PII redaction
- Citations
- Your cloud or VPC
- Audit logs
Technology That Fits the Problem
We choose models and tools based on your data and goals, not because they're fashionable.
Orchestration
- LangChain
- LlamaIndex
- Python
Vector Databases
- Pinecone
- Weaviate
- pgvector
- FAISS
Models and Embeddings
- OpenAI
- Claude
- Gemini
- Hugging Face
- Llama
Search
- Elasticsearch
- OpenSearch
- Hybrid search
- Reranking
Ingestion
- Airflow
- OCR and document parsers
- Kafka
Cloud and Evaluation
- AWS
- Azure AI
- GCP Vertex AI
- RAGAS
Not Sure Where to Start?
Tell us where you are and what you need. We will suggest a starting point.
You're probably looking for
Choose a stage to see our suggestion
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How Can We Work Together?
Whether you need a full AI product team or dedicated engineers to extend your own, we match the engagement to your situation.
Build My AI Solution
End-to-end discovery, data engineering, development, evaluation, deployment and monitoring.
Best for: Startups and businesses building a new AI product or feature.
Extend My AI Team
Dedicated AI engineers, ML engineers and data engineers who work inside your process.
Best for: Companies that already have data, a product or a team.
Explore With a Proof of Concept
A short, focused build or consulting sprint to test an idea before you commit to a larger investment.
Best for: Teams that are not yet sure how far this can go.
Choose How You Pay
Dedicated Team
Monthly retainer for long-term AI product development or ongoing improvement, with predictable billing.
- Full-time dedicated AI engineers
- Daily standups and sprint planning
- Maximum cost efficiency
Fixed-Price Project
For well-scoped AI projects with clear deliverables. Agree on price, timeline and milestones up front.
- Clear scope and milestones
- Fixed budget, no surprises
- Defined delivery dates
Flexible Hourly
Pay only for hours worked. Best for proofs of concept, evaluations, short sprints or expert consultation.
- No long-term commitment
- Transparent time tracking
- Scale up or down any time
Why Companies Work With D2i
Our teams do not just build AI, they solve real business problems with measurable outcomes.
Five Disciplines Under One Roof
AI, development, security, accessibility and QA from one team instead of piecemeal vendors.
Built Around Outcomes
Every engagement is measured against business results, not demo-day applause.
Security and Quality
ISO 27001 and ISO 9001 certified processes behind every engagement.
Tested Before It Ships
In-house QA and security testing for AI behavior, not just application code.
Global Delivery
India-based engineering with experience serving clients across the USA and beyond, at up to 60% savings versus onshore teams.
Long-Term Partnership
SLA-backed support and maintenance after launch. We do not disappear after go-live.
What Clients Say
In recognition of exceptional performance, dedication, hard work, passion, and commitment to excellence — D2i Technology’s invaluable contribution continues to make a significant impact in support of our All Hazards, One Health, One Nature mission.
Allison A. Sakara
Co-Founder & Executive Director, High Alert Institute
Their DevOps Services in USA helped us significantly reduce deployment time and infrastructure costs. D2i Technology streamlined our CI/CD pipelines and improved system stability. The results were visible within weeks, and their DevOps expertise truly made a difference.
DevOps Services & Solutions (USA)
D2i Technology is a highly dependable Web Development Company in India. From requirement gathering to final delivery, their team demonstrated strong technical expertise and ownership. The final product was robust, user-friendly, and built exactly as envisioned.
Web Development Company (India)
Frequently Asked Questions
The questions we hear most before a project starts.
Related AI and Engineering Services
Explore the services that work alongside RAG Development.
AI Development
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Agents that plan, use tools and complete multi-step tasks. Learn more about AI Agent DevelopmentWeb App Development
Build the product around your RAG assistant. Learn more about Web App DevelopmentDevOps and MLOps
Deployment, monitoring and scaling for production AI. Learn more about DevOps and MLOpsReady to Build AI That Answers From Your Data?
Tell us what questions you want answered. We'll help you understand the right architecture, team and next steps.
No obligation. Start with a 30-minute discovery conversation.