Agomonia LabsAgentic AI Platform Studio
Products
Agomonia Labs products prove the platform across document intelligence, video intelligence, finance and tax readiness, restaurant intelligence, sports analytics, cultural knowledge, and operational workflows.
Foundational Product
DocIntel turns static documents, transcripts, audio, and videos into a secure, searchable, conversational knowledge base with hybrid retrieval, citations, timestamp-aware sources, summaries, multilingual voice/chat, and vertical agent workflows for healthcare, restaurants, real estate leases, finance and tax readiness, and other document-heavy operations. The platform combines rules for precision, embeddings for discovery, AI for reasoning, workflow orchestration for consistency, and human review for trust.
How DocIntel Works
DocIntel combines OCR, layout understanding, table extraction, video metadata processing, sampled frames, timeline segmentation, semantic retrieval, and LLM reasoning to help teams ask questions, summarize long content, compare knowledge sources, and run domain-specific workflows. Every response is grounded in retrieved evidence and can be traced back to the original source, including timestamps for processed videos.
Executive summaries, section summaries, risks, obligations, timelines, and key decisions from long documents.
Side-by-side contract, policy, report, claim, proposal, or version comparison with cited evidence.
Business-specific rules, checklists, and output schemas for regulated and document-heavy work.
Video Intelligence Workflow
DocIntel treats video as an enterprise knowledge source, not a passive media file. The workflow routes uploads by file size, extracts metadata, frames, transcripts, and time segments, then turns the result into searchable RAG knowledge that can support chat, citations, summaries, and operational insights.
DocIntel Video Intelligence
DocIntel now supports videos as a first-class knowledge source alongside PDFs, scans, forms, transcripts, and voice workflows. Teams can upload trainings, meetings, inspections, walkthroughs, sports highlights, product demos, customer calls, and operational clips, then process them into timestamp-aware knowledge that works with the same RAG and chat foundation.
The workflow handles direct browser-to-GCS upload for larger videos, creates a video document record, extracts technical metadata such as duration, resolution, codec, bitrate, frame count, and audio availability, samples frames with bounded controls, builds timeline segments, captures transcript or audio signals when available, generates visual captions, stores chunks and metadata, and embeds video chunks into pgvector for grounded Q&A.
Open on YouTubeUpload PDF, DOCX, CSV, images, and text. Extract content, OCR scanned pages, classify, detect language, redact PII, and store originals in cloud storage.
Upload videos through normal or direct-to-GCS paths, process ffprobe metadata, sample frames, create captions and timeline chunks, and embed the results into the same knowledge base.
Combine pgvector semantic search with PostgreSQL full-text search and Reciprocal Rank Fusion, then re-rank candidates for better context.
Ask questions across selected documents and receive cited answers with source previews, markdown tables, privacy mode, and persistent chat history.
Create executive, key-point, section, detailed, and custom summaries. Large documents use map-reduce streaming for coverage.
Trace every question through retrieval, prompts, tool calls, model output, feedback, evaluation scores, and admin audit history.
Run domain workflows that read retrieved evidence, extract structured output, apply deterministic rules, use semantic discovery, preserve traceability, and support human approval gates.
DocIntel Ingestion Workflow
This walkthrough shows how DocIntel ingests files, validates security, extracts content, enriches metadata, creates embeddings, indexes governed knowledge, and connects the result to search, chat, agents, analytics, and business workflows.
Demo Narration
The demo story follows the full ingestion lifecycle: accept business files, validate and secure them, extract usable content, enrich metadata, create embeddings, index knowledge, and prepare the result for search, chat, analytics, agents, and workflow automation.
PDF, Word, Excel, PowerPoint, images, emails, and text files enter the workspace.
File type checks, malware scanning, governance policy checks, and metadata capture run first.
Text, tables, images, and document metadata are extracted, with OCR applied when needed.
Content is standardized into a consistent structure for downstream processing.
Summaries, classifications, keywords, entities, and business metadata are generated.
Documents are segmented into semantic chunks and transformed into vector embeddings.
Structured content, metadata, and embeddings are indexed for fast search and retrieval.
PII detection, redaction, retention policy, audit tracking, and traceability are applied.
Users can search, chat, summarize, analyze, and retrieve insights from ingested content.
Enriched knowledge connects to business workflows, vertical agents, analytics, and AI applications.
Retrieval, Chat, Evaluation, and Governance
This walkthrough explains hybrid retrieval, grounded chat, summaries, document comparison, answer evaluation, audit logs, and traceability. It shows how DocIntel moves from retrieved evidence to cited answers, quality checks, and a reviewable history of every AI interaction.
Demo Narration
The demo story is organized as a sequence of production behaviors: retrieve the right evidence, answer from that evidence, summarize and compare content, evaluate quality, and preserve the audit trail.
Semantic vector search and exact full-text search work together, then ranking brings forward the strongest evidence.
Users ask questions in natural language and receive answers grounded in retrieved document context with source citations.
DocIntel produces executive, detailed, section-level, and custom summaries from long documents or selected content.
Teams compare contracts, policies, reports, or document versions to find differences, missing items, obligations, and risks.
Responses and workflow outputs are checked for relevance, completeness, citation quality, faithfulness, and useful format.
Admins can review user, workspace, timestamp, question, answer, feedback, and workflow activity for governance.
Every important AI interaction can be traced through retrieved chunks, ranking, prompt context, model response, and cited sources.
Restaurant owner/member audio intake in English, Spanish, Bangla, Hindi, or Arabic. Extract profile details and menu prices, approve rows, then let customers search, compare, add menu items from chat, and pay for carryout orders through Stripe Checkout.
Responsive web and mobile access lets customers, restaurant owners, healthcare staff, and business users continue conversations, review documents, place orders, check summaries, and manage workflows from phone, tablet, laptop, or desktop browsers.
Cricket assistant with live web scraping, latest scorecards, team stats, player stats, rules retrieval, standings, LLM-as-judge evaluation, and text/voice conversation in English, Bangla, Hindi, Arabic, Spanish, and Urdu.
Rabindra Sangeet AI assistant with Bengali search, raag/taal filters, notation, voice, and evaluated answers.
Food recommendation assistant that uses restaurant discovery, approved menu data, dish price comparison, voice search, rating badges, verified feedback, and ranking agents.
Financial documents move through a repeatable workflow from intake to intelligence, readiness views, advisor packet PDF creation, approved packet upload, and human approval.
Finance workflow that starts with Tax Submission Readiness and extends into Financial Planning Readiness. It combines OCR, classification, embeddings, deterministic extraction, regex, AI reasoning, missing-item detection, prior-year comparison, net worth and cash-flow snapshots, human review, CPA/EA packets, advisor packet PDF creation, approved packet upload into the workspace, and advisor-ready planning packets across tax returns, brokerage statements, retirement records, mortgage documents, bank statements, credit cards, property records, and client notes.
Customers can submit text or voice feedback on restaurants, menu items, or verified carryout orders. AI suggests rating scores, sentiment, and tags such as taste, value, portion, freshness, spice, packaging, wait time, and accuracy.
Reference architecture for POS, inventory, customer experience, locations, memory, and natural-language operations analytics.