Even well-organized enterprises struggle to find the right file when it is buried across SharePoint, Google Drive, Slack, and internal tools. Pinnasys uses RAG to build AI-powered enterprise search solutions that return grounded answers from your data in seconds.
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Trusted by companies scaling with AI
Information is scattered across documents, emails, databases, and people's heads. A connected knowledge layer replaces repeated searching with answers employees can verify and use.
Not an edge case. A third of the workforce reports difficulty locating what they need to do their job, across organizations that have already invested in search.
Gartner Digital Worker Survey, 2024Half of employees now use tools like Copilot and Gemini primarily to find data. More than a third of them still struggle. The assistant is not the problem. The knowledge underneath it is fragmented and unmanaged.
Gartner Digital Worker Survey, 2024Gartner's Market Guide repositions enterprise search as the foundational platform powering AI assistants and agents, rather than a downstream productivity tool. What the agent retrieves determines what the agent can do.
Gartner, Market Guide for Enterprise AI Search, 2025–2026From internal knowledge bases to customer-facing search, we build AI-driven enterprise search solutions that understand meaning, not just keywords.
Retrieval-augmented generation searches documents, databases, and SharePoint to produce grounded answers with citations, using hybrid retrieval, reranking, and prompt orchestration so each response traces back to a real source.
Employees ask questions in plain language and receive answers from policies, SOPs, product documents, and institutional knowledge, backed by ingestion pipelines, embeddings, and access controls.
Document intelligence pipelines read, classify, extract, and summarize contracts, reports, RFPs, and claims, turning static PDFs into queryable knowledge without manual review.
We map relationships between products, customers, contracts, suppliers, and regulations into a queryable knowledge graph that supports multi-hop questions flat retrieval misses.
Every stage ends with something you can check, and each one has to earn the next.
AUDIT
Some teams know where their content lives. Others find out here. We inventory the sources, formats, and permission models, and surface what nobody had accounted for.
BUILD
Connect the sources, then clean, classify, chunk, and enrich the content. We build retrieval, reranking, and answer generation on top, with citations that resolve back to the source.
MEASURE
We release to the first user group with monitoring, support, and training, then compare against the baseline set at the audit: did the right answers show up, did trust in the results hold up in real use.
SCALE
With the case proven, we optimize what is already working and extend the same system to more sources, more teams, and more of the business.
Every engagement started the same way: the answer existed somewhere, and nobody could find it. Here is what changed once search could read across the systems it was buried in.
30%
More Booked Appointments
2x
Team Productivity
95%
Prediction Accuracy
50%
Less Downtime
80%
Faster Invoice Processing
25 hrs
Data-entry Time Saved Weekly
12-month
Roadmap With Real Cost Estimates
8 weeks
Delivery, Single Consultant
50%
Reduction in Admissions Processing Time
15 hrs
Admin Time Saved Weekly
Search only earns its place if team find the answer, trust it, and act on it. Here's what teams told us changed.
Esra Erciyas
Senior Product Manager, Commercetools
We'd been optimizing search and visual discovery without a reliable benchmark. Pinnasys built one: 10,000 product records, 3,000 images, every item labeled to our taxonomy and double-reviewed. What impressed me was how disciplined they were about the edge cases.
Tell us your primary goal, and we will guide you on how to achieve it.
Credentials
Trust begins before a question is asked. We enforce access at retrieval time, ground answers in approved sources, and preserve an audit trail across the search lifecycle.
SOC 2 Type II
GDPR
EU AI ActSOC 2 Type IIGDPREU AI Act
ISO 27001
HIPAA
PCI DSSISO 27001HIPAAPCI DSS
ISO 42001
CCPAISO 42001CCPAThe same small pod scopes your use case, builds the system, and stays with you through production. All of our AI engineers are Claude-certified.
Designs the system, the model choice, and the guardrails it runs inside.
Builds it, plus the evaluation suites that prove it works before launch.
Certified on Claude foundations, prompting, and safe deployment.
Build custom AI applications, automation workflows, and the systems that connect them to your business — staffed by the people who advised you.
Build custom AI applications, automation workflows, and the systems that connect them to your business.
Where they focus
Build retrieval that returns the passage answering the question, not the document it sits in.
Where they focus
Connect the systems that hold your content and prepare it so retrieval can actually find things.
Where they focus
Make sure nobody sees a document they should not, and that every answer can be traced back to its source.
Where they focus
The strongest enterprise search experiences combine natural-language understanding, traceable answers, flexible connectors, and access-aware retrieval in one governed layer.
Each implementation starts with governance, source ownership, and the decisions employees need to make. The retrieval layer then adapts to the language, risk, and workflows of the industry.
Put the right SOP, the right revision, and the maintenance history in front of a technician on the floor.
Explore AI Enterprise Search for Manufacturing & Industrial solutionsResolve returns, catalog, and policy questions in one answer instead of four tabs and an escalation.
Explore AI Enterprise Search for Retail & Ecommerce solutionsFind lender criteria, compliance rules, and customer history without opening four systems, with results scoped to what each role may see.
Explore AI Enterprise Search for Financial Services & Insurance solutionsRetrieve clauses, precedent, and matter history across contracts and filings, with a citation on every result.
Explore AI Enterprise Search for Legal solutionsGive clinical and admin staff the current protocol, not a version from two revisions ago, with permissions respected on every result.
Explore AI Enterprise Search for Healthcare solutionsAnswer carrier terms, shipment history, and supplier agreement questions without chasing the person who filed them.
Explore AI Enterprise Search for Supply Chain & Logistics solutionsLet staff and students find policy, course, and administrative answers without emailing three departments.
Explore AI Enterprise Search for Education solutionsPull lease terms, property records, and transaction history out of scattered folders and into one answer.
Explore AI Enterprise Search for Real Estate solutionsGive front-line staff instant answers on rates, policies, and guest history instead of putting someone on hold.
Explore AI Enterprise Search for Travel & Hospitality solutionsSearch quality depends on more than a model. Our team engineers the data, retrieval, evaluation, security, and operating practices needed for dependable production use.
We identify the questions, users, and decisions that matter before selecting models, vector stores, or frameworks.
Retrieval quality, source authority, and citation fidelity are designed before the answer experience is polished.
Identity, permissions, and source access are enforced when evidence is selected, not added as an afterthought.
We use indexed, federated, or hybrid patterns depending on source size, freshness, latency, and governance needs.
Evaluation sets, relevance metrics, hallucination tests, and user feedback create a clear path for improvement.
Pinnasys supports deployment, adoption, monitoring, and expansion after the first production use case goes live.
Our AI experts select the retrieval, generation, data, and observability components that best fit your AI knowledge base and production environment.
Models
Anthropic Claude
OpenAI GPT
Google Gemini
Meta Llama
Mistral AI
Hugging FaceAnthropic ClaudeOpenAI GPTGoogle GeminiMeta LlamaMistral AIHugging FaceAgents & Orchestration
LangGraph
CrewAI
Microsoft AutoGen
AWS Strands AgentsLangGraphCrewAIMicrosoft AutoGenAWS Strands AgentsIntegration & Automation
MCP
n8n
Temporal
Apache Airflow
Microsoft Power Automate
ZapierMCPn8nTemporalApache AirflowMicrosoft Power AutomateZapierEvaluation & Guardrails
NVIDIA NeMo Guardrails
AWS Bedrock Guardrails
LangSmith
Langfuse
RagasNVIDIA NeMo GuardrailsAWS Bedrock GuardrailsLangSmithLangfuseRagasEvery certification, ranking, and partnership we highlight is independently verifiable.
100% Job Success
Across client workflows & AI system
Across client workflows & AI systems
Top AI Company Jaipur
Certified Cloud Deployment
From practical architecture choices to AI knowledge management and governance.
Answers to the technical, security, and deployment questions enterprise buyers ask before they invest.
Ask us directlyTraditional enterprise search returns a list of documents to open. Generative AI enterprise search returns a direct answer created from your own data through RAG, with source citations. It understands meaning, handles multi-part questions, and can combine evidence across documents.
The system can index documents, PDFs, spreadsheets, emails, wiki pages, CRM records, ticket histories, and structured database tables. Common integrations include SharePoint, Confluence, Notion, Google Drive, Slack, Salesforce, Microsoft Teams, and internal tools.
Answers are generated from retrieved source documents rather than relying only on a model's pre-trained memory. We add citation enforcement, confidence scoring, evaluation sets, and fallback responses so the system can state uncertainty instead of producing an unsupported answer.
Most focused deployments can go live in 6 to 10 weeks. We begin with one use case, such as policy lookup or product documentation, then expand after accuracy, adoption, and security checks pass internal review.
The search layer can inherit your existing permission structure from SharePoint, Google Workspace, and identity providers. Users receive answers only from documents they are authorized to access.
Test the demo with real questions and real permission scenarios. Evaluate retrieval relevance, citation accuracy, response to missing evidence, source freshness, latency, connector coverage, and admin controls.
The best fit depends on source systems, security requirements, data freshness, query volume, user experience, and whether you need indexed, federated, or hybrid retrieval.
Whether you operate in e-commerce, finance, healthcare, insurance, or technology, AI enterprise search can save teams hours every week.
What you send us
A roadmap, a build, an integration, or someone to run what's already live. Whichever you need, a rough description is enough.
A 30-minute call
We work through your operations, your data, and where the payback is clearest. No cost, no obligation.
Your plan
What we'd build or run, what it costs, and how long it takes. Yours to keep, including the honest answer if a simpler fix would serve you better.
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