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Atal AI
Citation-Grounded AI

Accurate customer answers grounded in truth, never hallucinated

When an AI chatbot invents a discount code or return policy, your business pays the cost. Atal AI retrieves exact verified passages from your own manuals, contracts, and knowledge base with mandatory inline source citations.

πŸ›‘οΈ No credit card required β€’ 5-minute setup β€’ Free tier available

Customer Query

Can I return an item 45 days after delivery?

Grounded AI Response (Confidence: 99.4%)

Our standard return window is 30 days from delivery. After 45 days, returns can only be accepted if the item is defective under the 1-year manufacturer warranty.

Source: Return_Policy_2026.pdf (Section 3.2, p. 4)View chunk snippet
πŸ›‘οΈ Sourced directly from your uploaded documentation

Closed-Domain

Grounded Answers

Refuses when the answer isn't in your sources

Attributed

Source Citations

Passages cite matching documentation passages

Hybrid

Dense & Sparse Search

Hybrid vector search (BGE-M3) and BM25 keyword matching

24/7

Availability

Customer inquiries resolved without waiting for human availability

Enterprise RAG Architecture That Protects Your Brand

Built for companies where a wrong answer causes legal, financial, or reputational damage.

Retrieval Quality

Dense & Sparse Hybrid Semantic Search

Combines dense neural embeddings (BGE-M3) with exact keyword matching (BM25). Whether a customer searches by conceptual symptom or specific SKU part number, the correct section is located instantly.

  • βœ“1024-dimensional semantic dense vectors
  • βœ“Exact keyword match for technical SKUs & error codes
  • βœ“Automatic language-agnostic cross-lingual matching
Autonomous Execution Trace

POST /v1/agent/action-dispatcher

βœ“ Security assertion: OK

βœ“ Permission boundary: VALIDATED

βœ“ Transaction status: COMMITTED

Relevance Scoring

Cross-Encoder Reranking Layer

Top candidates from initial retrieval pass through a high-precision cross-encoder reranker that evaluates context relevance against the query before LLM prompt injection.

  • βœ“Filters out marginal or out-of-date document chunks
  • βœ“Ensures highest priority policies always take precedence
  • βœ“Reduces prompt token costs and generation latency
Autonomous Execution Trace

POST /v1/agent/action-dispatcher

βœ“ Security assertion: OK

βœ“ Permission boundary: VALIDATED

βœ“ Transaction status: COMMITTED

Guardrails

Explicit Refusal & Graceful Escalation

When retrieved documents do not contain the answer, Atal AI never guesses. It politely states it does not know, captures the customer’s contact details, and routes the ticket to your human team with full transcript history.

  • βœ“Configurable confidence score refusal threshold
  • βœ“Automatic lead capture on unknown inquiries
  • βœ“Gaps automatically surfaced in the Knowledge Gaps report
Autonomous Execution Trace

POST /v1/agent/action-dispatcher

βœ“ Security assertion: OK

βœ“ Permission boundary: VALIDATED

βœ“ Transaction status: COMMITTED

The Grounded Knowledge Lifecycle

How your documents become verified customer answers in seconds.

STEP 1

Ingest & Chunk

Upload PDFs, text, or crawl URLs. Text is parsed, split into 500-token semantic chunks, and embedded.

STEP 2

Hybrid Retrieval

Incoming customer questions trigger simultaneous vector similarity search and exact keyword lookups.

STEP 3

Rerank & Filter

Cross-encoder scores candidate chunks. Only chunks clearing confidence thresholds are passed to the model.

STEP 4

Synthesize with Citation

The model drafts a clear answer citing exact source documents, or escalates if information is missing.

Frequently Asked Questions

Clear answers to common questions about security, pricing, and integrations.

How does Atal AI avoid hallucinations?

Atal AI operates on closed-domain grounded retrieval. It is strictly constrained to the text extracted from your uploaded documents and website crawls. If the retrieved context does not clear confidence thresholds, it refuses to guess and transfers to an agent.

What file formats and sources can I upload?

You can upload PDFs, Word documents (DOCX), plain text files, markdown, and spreadsheet tables, or simply point our crawler at your public documentation and help center URLs.

Does it support multilingual questions and answers?

Yes. The underlying embedding model (BGE-M3) and LLM architecture natively understand cross-lingual semantic matching across 100+ languages.

What happens when content in my documentation changes?

Re-uploading or updating a document triggers instant chunking and vector re-indexing. Deprecated chunks are purged from vector memory immediately.

Never let an AI invent your company policy again

Upload your documents in minutes and provide 24/7 grounded support to your customers.

Free tier included β€’ No credit card required β€’ Credentials encrypted (AES-256-GCM)