RAG Development Services for Accurate Hallucination-Free Enterprise AI
Improve customer satisfaction, prevent AI hallucinations, and enhance AI accuracy by training LLMs on proprietary, secure enterprise-specific data.
Harness the power of your enterprise’s vast knowledge source through LLMs enhanced with retrieval-augmented generation.
Off-the-shelf generative AI tools have failed to live up to the hype, as they are trained on limited information and produce generic responses. At SHALIGRAM, our RAG development services enable organizations to deliver fine-tuned, cited responses to employees/customers while maintaining retrieval quality and production reliability.
Top consulting firm McKinsey’s research emphasizes RAG as a foundational bridge for the trust gap that enterprises face. We help organizations build RAG systems that scale reliably in real-world complexity.
Challenges we solve with RAG development services
AI hallucinations
We build the RAG data ingestion and grounding infrastructure from scratch, and enforce citations to reduce hallucinations.
Disconnected business knowledge
We develop a unified retrieval layer that connects fragmented data silos without the need to rebuild the existing tech stack.
Information overload
We perform data audits, purge obsolete files, categorize user questions, and ensure high-precision retrieval.
Legacy knowledge systems
We implement non-invasive ingestion and data-remediation pipelines that bridge old infrastructure with modern vector search.
Slow decision-making
We help remove decision bottlenecks, unify critical data, and verify facts by deploying knowledge hubs.
Low employee productivity
Our experts build knowledge assistants and intelligent agentic workflows that eliminate the hours employees spend looking for information.
Retrieval-Augmented Generation (RAG) development services
RAG consulting
We operate at the intersection of business strategy, data governance, and high-level enterprise architecture by focusing on legacy bridging, preventing expensive pilot failures, calculating ROI, and defining corporate guardrails. We calculate the total cost of ownership for RAG infrastructure, prioritize corporate pipelines, and create guidelines to manage “content drift”
Custom RAG application development
We design AI pipelines for your enterprise that safely connect LLMs to your internal, proprietary company data, tailored to specific data and use cases. Custom RAG implementation helps avoid the expense of repeatedly retraining or fine-tuning underlying language models, while protecting proprietary intellectual property and complying with governance frameworks.
Enterprise RAG solution development
We specialize in building highly scalable, secure, and compliant RAG systems tailored to minimize hallucinations and ensure intellectual property safety, while increasing employee productivity. Our core development phase includes advanced data engineering, pipeline setups, and hybrid search and vector architecture development.
AI knowledge base development
We help you achieve context-aware information retrieval through our services that include a rigorous, end-to-end framework designed for your enterprise’s scalability. We identify specific high-value areas, catalog unstructured data sources, and construct automated connectors to ingest data periodically, and implement re-ranking models to surface only the most accurate sources.
Enterprise AI assistant development
We save employee time spent searching through fragmented databases by engineering permission-aware corporate intelligence systems. We follow a structured development lifecycle, engineering pipelines, advanced retrieval infrastructure, and custom agentic architectures to manage the flow of user queries and program specialized sub-agents.
RAG integration
We create reliable, context-aware applications by integrating the RAG retrieval engine with active enterprise directories. We deploy ETL connectors, set up and tune enterprise vector databases, and integrate hybrid search and reranking algorithms to pull the most relevant data points instantly.
Our RAG capabilities that build intelligent AI ecosystems
Intelligent document retrieval
We use a combination of advanced parsing, hybrid search, and precise context reranking to retrieve documents.
Semantic search
We go beyond simple vector matching to ensure contextual relevance and high retrieval precision.
Hybrid search
We build, deploy, and scale specialized architectures and bridge the gap between keyword precision and contextual awareness through hybrid search.
Multi-document reasoning
We implement agentic RAG patterns to close information gaps spread across separate documents.
Real-time knowledge updates
We engineer specific real-time knowledge update architectures to remove lags that result in stale responses.
Source citation
We develop retrieval engines that maintain a metadata chain-of-custody, and every chunk of text is mapped to its precise source.
RAG solutions we build
Our enterprise knowledge assistant solutions are engineered across distinct functional layers to ensure security, high retrieval precision, permissions compliance, and continuous data synchronization.
Our numbers reflect our commitment
Enterprise use cases by industry
Healthcare
Our services focus on using custom medical tokenizers and chunking methodologies to ensure that complex scientific relationships, drug interactions, and medical acronyms maintain their contextual meaning. We build RAG models that map internal clinical data lakes alongside public research databases and flag low-certainty retrievals to protect clinical integrity.
- Clinical knowledge assistant
- Medical research & literature search
- Patient support chatbot
- Hospital SOP & policy assistant
- Healthcare documentation search
- Medical coding & compliance assistant
Manufacturing
We empower manufacturing industries that grapple with vast archives of outdated engineering blueprints, standard operating procedures (SOPs), and IoT telemetry through RAG systems capable of processing multimodal inputs—such as CAD files, scanned maintenance logs, and schematics.
- Production knowledge assistant
- Equipment maintenance & troubleshooting assistant
- Quality control documentation search
- Standard operating procedures (SOP) assistant
- Engineering documentation assistant
- Supplier & procurement knowledge search
Fintech
Our solutions are designed for the high-velocity data retrieval and extreme accuracy needs of payments apps, digital lending platforms, and trading platforms. We integrate real-time API and database connectors alongside RAG retrieval to surface multi-currency balances and transaction data.
- Financial research assistant
- Investment knowledge platform
- Regulatory compliance assistant
- Fraud investigation knowledge search
- Customer financial support assistant
- Internal policy & documentation assistant
Logistics and supply chain
We develop RAG systems capable of handling highly multimodal inputs and spatial telemetry. We establish Vision-LLM RAG networks for reading unstructured shipping documentation, and develop RAG agents that guide decisions in case of supply chain breakdowns.
- Shipment & logistics knowledge assistant
- Warehouse operations assistant
- Supply chain documentation search
- Vendor & procurement knowledge base
- Customs & compliance assistant
- Fleet operations knowledge assistant
BFSI
We help banks, insurers, and NBFCs deal with legacy core-banking systems, mainframe infrastructure, and intense regulatory audits with BFSI-specific RAG implementations. Our experts develop retrieval algorithms that prevent data leakage by enforcing permission-aware retrieval that filters restricted documents out of the retrieval set before any content reaches the LLM.
- Banking knowledge assistant
- Insurance claims support assistant
- Loan & mortgage documentation assistant
- KYC & compliance assistant
- Customer service AI assistant
- Risk & policy knowledge platform
Real estate
We help real estate companies manage lease portfolios, multi-jurisdictional zoning laws, and property underwriting. We turn this data into high-speed financial and transactional intelligence that flags unusual termination clauses, renewal options, or rent escalation metrics.
- Property knowledge assistant
- Lease & contract intelligence
- Real estate document search
- Property management AI assistant
- Client inquiry assistant
- Legal & compliance knowledge base
Retail and eCommerce
We enable conversational commerce and real-time product catalog & inventory sync along with hyper-personalized recommendations based on past purchases. We integrate RAG with order management systems for shipping updates, tracking, and returns.
- Product knowledge assistant
- Customer support AI assistant
- Inventory & catalog search
- Return & refund policy assistant
- Vendor knowledge management
- Internal operations knowledge base
Food and beverages
We deploy RAG architectures to solve the complex operational, compliance, and supply chain challenges in the F&B industry, and connect LLMs with proprietary ERP, IoT, and regulatory databases.
- Food safety & compliance assistant
- Recipe & product knowledge search
- Restaurant operations assistant
- Supply chain documentation assistant
- Quality assurance knowledge base
- Employee training assistant
Oil and gas
We help the oil and gas sector to connect disparate silos across drilling, production, and supply chain procurement using intelligent routing and knowledge graphs. Our experts build pipelines that process messy data, seismic logs, and enforce role-based access controls.
- Technical documentation assistant
- Equipment maintenance knowledge base
- Health, safety & environment (HSE) assistant
- Regulatory compliance assistant
- Field operations knowledge search
- Engineering standards & SOP assistant
Our RAG development process
Discovery and assessment
We conduct data audits to check data quality, map use cases, and define KPIs.
Data preparation
We connect enterprise data repositories, perform document conversions, and eliminate duplicate versions.
Database setup
We select a multi-tier architecture and configure and organize specialized vector databases.
RAG pipeline integration
We link the database to LLMs and integrate the RAG system into enterprise apps or websites.
Testing
We minimize hallucinations through end-to-end testing and user acceptance testing.
Monitoring
We monitor systems for errors or new data gaps, and refresh the database regularly with the newest enterprise data.
Why choose SHALIGRAM for RAG development
Building production-grade enterprise knowledge systems
We empower our clients through RAG development services rooted in rigorous data grounding and clear source citations. We are known for implementing dynamic, self-updating retrievals through intelligent enterprise knowledge systems.
- Advanced retrieval engineering
- Implementation of automated testing frameworks
- Ability to orchestrate agentic RAG systems
- Compliance with industry-specific regulations
Tired of outdated AI tools that bring up answers your team can't trust?
Deploy our RAG-enhanced enterprise systems to minimize hallucinations by grounding every response in your enterprise data.
FAQs
Trusted by businesses around the world for their digital transformation journey.
In RAG, relevant information is retrieved and added to the model’s input context at the time of query, whereas fine-tuning permanently updates the model’s weights on particular data.