Agomonia LabsAgentic AI Platform Studio
Cloud Native Architecture
Agomonia Labs is designed with a modular, cloud-native architecture that separates stateless request handling, durable memory, retrieval indexes, file storage, agent execution, evaluation, and governance, allowing every layer to scale, evolve, and operate independently.
DocIntel Platform Architecture
DocIntel is Agomonia Labs' intelligence platform for turning unstructured documents, transcripts, audio, and videos into reliable business answers. It combines OCR, layout understanding, table extraction, video metadata processing, frame sampling, timeline chunking, semantic retrieval, and LLM reasoning to support question answering, summarization, comparison, video Q&A, and domain-specific workflows. Every response is grounded in retrieved evidence and can be traced back to the original source, including timestamps for processed videos.
PDFs, scans, forms, reports, contracts, policies, recordings, trainings, meetings, walkthroughs, and enterprise media.
Text, tables, layout, sections, entities, dates, video metadata, frames, captions, transcripts, and timestamps are understood.
Extracted knowledge is chunked, embedded, and stored for hybrid retrieval.
AI retrieves the right evidence for answers, summaries, comparisons, and structured outputs.
Outputs stay traceable and can trigger repeatable business processes.
Document Intelligence Lifecycle
DocIntel presents a simple experience for business users while powerful engineering works underneath. From the outside, the flow is easy to understand: enterprise documents and videos are ingested, important content is extracted and structured, knowledge is indexed for search, and AI uses that trusted context to generate cited answers, timestamped video answers, summaries, comparisons, and workflow outputs.
Behind that simple experience is a deeper technical foundation: direct-to-GCS large video upload, ffprobe metadata extraction, bounded ffmpeg frame sampling, optional visual captioning, optional audio transcription, OCR, layout parsing, table extraction, deterministic rules, regular expressions, semantic chunking, vector embeddings, metadata storage, hybrid retrieval, agent orchestration, evaluation, audit logs, and governance controls. This balance lets DocIntel use rules for precision, embeddings for discovery, AI for reasoning, workflow orchestration for consistency, and human review for trust. The public website keeps the diagram business-friendly, while detailed architecture views can be used in technical documentation, engineering discussions, investor material, or enterprise implementation reviews.
Upload PDFs, scans, forms, reports, contracts, policies, enterprise documents, transcripts, audio files, and videos.
Extract text, tables, layout, sections, entities, dates, video metadata, sampled frames, transcript signals, captions, and timestamps.
Chunk, embed, and store knowledge in a searchable retrieval layer.
Retrieve evidence and generate answers, summaries, comparisons, and structured outputs.
Trace answers back to documents, pages, sections, and extracted evidence.
Turn document intelligence into repeatable domain workflows.
Condense long documents into executive summaries, section summaries, risks, obligations, timelines, and key decisions.
Compare contracts, policies, reports, claims, proposals, or versions side by side with highlighted differences and cited evidence.
Convert recordings into metadata, frame samples, captions, transcripts, timeline chunks, embeddings, timestamp-aware citations, and video Q&A.
Apply business-specific rules, checklists, and output schemas for legal, insurance, finance, healthcare, operations, and compliance use cases.
Identity Management and Security
DocIntel identity management is designed so users can enter the platform through a controlled signup and login flow before they reach sensitive document intelligence, chat, workflow, billing, or administrative areas. Signup captures the account information needed to create the user profile and connect the user to the right workspace, while login verifies the user before any protected DocIntel capability is available.
Multi-factor authentication adds a second verification step beyond the password. This reduces the risk of unauthorized access and makes DocIntel more appropriate for document-heavy and workflow-heavy environments where teams may handle contracts, healthcare documents, lease records, restaurant operations, billing context, or other sensitive business information.
After authentication, DocIntel uses workspace scoping, role-based access control, audit history, and governance-aware workflow rules so each user sees only the data and actions allowed for their role. Admins, contributors, reviewers, operators, clinicians, patients, restaurant owners, staff, and other personas can be mapped into permission boundaries while traceability remains available for security review.
Open identity demoCreate a user account and connect the user to the appropriate workspace or product access path.
Validate user credentials before protected document, chat, workflow, billing, and admin capabilities are available.
Require an additional verification step to reduce unauthorized access risk.
Apply RBAC, workspace scoping, audit history, and governance rules after authentication.
FastAPI runs on Cloud Run, so request capacity can scale horizontally while sessions, documents, vectors, and logs stay in managed stores.
Users, workspaces, documents, chat history, vectors, and agent runs are scoped so teams collaborate without crossing data boundaries.
ADK runners execute asynchronously, letting specialist agents call tools, retrieval systems, and live services without blocking the app.
pgvector, Firestore vector indexes, and full-text search keep semantic and exact-match retrieval fast as knowledge volume grows.
Video timelines are chunked, embedded, and cited with timestamps, so users can ask what happened in a recording and connect the answer with the rest of the workspace knowledge.
Long-running chat, summaries, and workflow outputs stream progress to the browser while backend services continue work safely.
MFA, trace IDs, audit logs, response evaluation, feedback, usage limits, privacy controls, RBAC, and approval gates keep scaled AI reviewable.