Turn your enterprise knowledge into
AI-powered answers your team can trust.

Unlock the intelligence trapped inside your PDFs, sheets, Sharepoint, and databases. We construct highly-engineered RAG pipelines that deliver answers in seconds, with strict permissions security and verified citations.

Start with an AI Sprint
PDFPDF Documents
Excel & Sheets
SharePoint Docs
Slack Archive
TMS Teams Logs
Salesforce CRM
Interactive Lab

Multi-Source Ingestion & Grounding Pipeline

Data Sources
Vendor_Agreement_2026.pdf
4.8 MB
Awaiting
Q4_Financial_Metrics.csv
12.4 MB
Awaiting
SOP_Support_Guidelines.html
245 KB
Awaiting
CRM_Customer_Logs.json
18.2 MB
Awaiting
Semantic Core
Standby
Generative Console
Retrieval-Grounded EngineGPT-4o Secure

Click Ingest on the top-right to submit prompt query.

Proven Pedigree| 16 Years Engineering350+ Enterprise ImplementationsPharmaBFSIFMCGManufacturingSaaSLogistics
Scattered Intelligence

The Quiet Cost of
Scattered Knowledge

Most enterprises sit on a decade or more of accumulated knowledge — SOPs, contracts, policies, research, manuals, training materials, support tickets, meeting transcripts, emails. The information your team needs to make decisions every day is already there. It just isn't reachable.

The cost shows up quietly, everywhere. New hires take months to ramp up. Support agents put customers on hold to dig through wikis. Sales reps rebuild proposals from scratch because they can't find the last good one. Compliance teams scramble during audits. And when senior people leave, their context leaves with them.

Traditional search doesn't solve this — keywords don't understand questions. Generic chatbots don't solve this — they hallucinate when they aren't grounded in your data. What works is a retrieval layer that reads across every format, finds the right passage, and answers with the source attached.

That is what we build.

25% wasted
Engineering Cycles Lost

Average amount of time spent by engineers manually searching through archaic wikis, ticket histories, and team silos instead of shipping high-impact code.

Wasted Engineering Cycles

Engineers spending 25% of their day manually digging through archaic, nested wikis and Slack logs instead of shipping code.

Glacial Team Onboarding

New hires taking 4–6 months to reach peak autonomy due to lack of a central, semantic intelligence layer that knows company systems.

Tribal Knowledge Rot

Critical business decisions stalling or relying on guesswork when core staff exit and operational memory remains untraced.

The Hallucination Nightmare

Standard LLM search bots confidently generating false legal details or incorrect product limits, endangering regulatory compliance.

Data Permissions Collapse

General search index tools leaking confidential executive salary sheets or payroll metrics to unauthorized staff segments.

Complex Layout Blindness

Simple out-of-the-box vector parsers completely scrambling complex corporate spreadsheet structures and scanned warranty PDFs.

Core Architecture

Production-Grade RAG Infrastructure

We bypass simple templates and engineer robust, enterprise-secure pipelines designed for 99%+ accuracy and high volume ingestion.

Ingestion Layer

Multi-Format Layout Parsing

Naive text extraction loses structure. We decompose complex PDFs, tables, diagrams, and transcripts into precise hierarchical segments prior to embedding.

Document_Layout_Analyzer v2.1OCR Mode Active
01_TABLE_1 (Data Grid)Merged 12 rows, 6 cols → Chunk-017
02_DIAGRAM_3 (Chart)Context: "Revenue Growth 2026" → Chunk-018
03_HEADER_H2 (Legal Terms)Inherits global permissions context → Chunk-019
Retrieval Strategy

Hybrid Sparse & Dense Engine

Combining deep-learning vector semantics with exact keyword index match (BM25) to catch contextual matches and direct SKU search flawlessly.

Dense Vectors (Semantic)Sparse BM25 (Keyword)
Dense Weight
0.65
Sparse Weight
0.35
Governance & Security

Enterprise Access Mapping

Inherits user security scopes straight from Salesforce, Azure AD, or SharePoint. Users can only query documents they are strictly authorized to view.

Executive_Comp_2026.pdfBlocked
IP_Patent_Strategy.pdfBlocked
Enterprise_SOP.docxVisible
Quality Assurance

Dual-Pass Grounding Verification

Automated dual-pass evaluator audits each LLM response against the source nodes. Any response that scores below the 95% faithfulness index triggers automatic revision.

Dual-Pass Shield Engine99.4% Faithful
Context Groundedness: 99.8%Coherence Metrics: 98.9%
Next-Generation Intelligence

Enter the Era of RAG 2.0

Moving beyond simple vector searches. We build reasoning systems that synthesize, deduce, and execute across multiple files and systems.

Step 01 / Phaseout
Naive Vector RAG

Plain vector queries with simple top-k lookup. High hallucination risk.

Step 02 / Standard
Hybrid Metadata RAG

Metadata tagging + keyword match. Better accuracy, but low contextual reasoning.

Step 03 / Advanced
Agentic Workflows

Multi-agent loops that plan, verify citations, and fetch live tool state dynamically.

Step 04 / State-of-the-Art
GraphRAG & Maps

Semantic graph relationships mapping across all documents. Deep structural queries.

GraphRAG & Knowledge Maps

We build semantic maps linking corporate terms. Ask complex queries like *"What contracts are impacted by our Q3 compliance update?"* and get fully synthetic multi-document answers.

Agentic Reasoning Loops

Our systems don't just search once. They run iterative planning loops, execute database calls, analyze results, self-correct, and verify claims recursively.

Multimodal Core Processing

Unstructured data goes beyond raw text. We embed layouts, scanned invoices, complex product charts, spreadsheets, and meeting audio recordings into unified searchable indices.

Integrations

If your team uses it, we can parse it.

No complex manual exports required. We deploy background pipeline maps that automatically read, chunk, and index live updates safely inside your cloud perimeter.

Unstructured Contracts & PDFs

SOPs, vendor agreements, legal policies, research catalogs, scanned mechanical manuals.

Dynamic Spreadsheets & Tables

Financial reserve sheets, product limit matrixes, inventory ledgers, structured CSVs.

Corporate CRMs & Databases

Salesforce account logs, support ticketing history, PostgreSQL/MongoDB records.

Emails & Exchange Logs

Customer communication logs, vendor exchanges, historical transaction chains.

SharePoint & Internal Wikis

Confluence team directories, engineering wikis, HR policies, security guidelines.

Slack & Teams Comms

Historical discussion archives, support channels, client resolution boards.

"If your team uses it to reference daily work, our pipeline will parse and vectorize it with citation mapping."

Live Console Playground

Experience Grounded Citation Answers

Click a corporate role below to trigger a typical prompt query, watch the grounding evaluation execute, and check citations in the slide-out drawer.

Nanostuffs RAG Console v3.4.1|Active Knowledge Graph
U
User Query
What is our standard SLA for Enterprise tier, and do we offer customized warranties?
Grounded AI AnswerConfidence: 99.4% Verified
Graph Entitiy Mapped: SLA, GDPR, Expenses, TelemetryHandled secure enterprise session
Engineering Pillars

Why Nanostuffs RAG Engineering?

We operate as an elite engineering team delivering custom, robust vector structures—not simple template integrations.

Decoupled Ingestion Engine

Our layout extraction models decompose scanned data, tables, and nested pages into clean markdown formats. We preserve hierarchies instead of chopping files into random word counts.

Hybrid Retrieval Tuning

We combine exact keyword index retrieval (BM25) with deep vector semantics. This guarantees exact matches for unique model SKUs, invoice IDs, or specific legal clauses.

Permissive Context Security

We inherit permission matrices from Azure AD, Okta, and Salesforce. A user query will never pull context tokens from a source document they aren't authorized to read.

Vendor/Model Agnostic Architecture

Deploy private instances of Claude 3.5 Sonnet, private Azure GPT-4o, or fully offline open-source models inside your secure VPC. Avoid API locked-in dependencies.

Obsessive Quality Observability

We bake dual-pass evaluation tools straight into the RAG routing layer. Real-time dashboards track faithfulness score, context recall, and groundness drift metrics.

15+ Years Enterprise Pedigree

We are certified enterprise engineers since 2011. We build RAG pipelines using strict CI/CD, complete schema validation, and audit controls that satisfy security teams.

Verified Metrics

Real outcomes from secure production systems.

99.4%

Context Groundedness Metric Certified

< 1.4s

Semantic Search & Vector Graph Latency Envelope

9.3 hrs

Average Saved Weekly Search Hours Per User Segment

Structured Delivery

Fixed Scope. Precise Execution.

We deliver through highly-structured, time-boxed milestones so your team achieves direct ROI without consulting drift.

Weeks 1–2Step 01

Discovery & Knowledge Mapping

We audit your data sources, document formats, permissions, and define high-ROI RAG use cases mapped to your systems.

Weeks 3–6Step 02

Ingestion & Pipeline Build

We build custom multi-format chunking, vector embedding, and hybrid sparse/dense retrieval pipelines over your live data.

Weeks 6–7Step 03

Observability & Guardrails Integration

We implement automated faithfulness evaluations, security controls, citation routing, and drift detection alerts.

Week 8Step 04

Production Launch & Enablement

We deploy the verified system in your cloud environment, enable team access with full governance, and transition ownership.

Build Your Private Pipeline

Stop digging manually.
Unlock your accumulated memory today.

Let's map your databases and unstructured documents in a structured 2-week discovery sprint to prove semantic accuracy before indexing live data.

Start with an AI Sprint