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Arcnem Vision

Arcnem Vision is an image-ingestion and analysis platform built around a server-side workflow engine. Images arrive through workflow API keys or the dashboard, workflows are loaded from database state, MCP tools perform the analysis, and the dashboard exposes the resulting documents, artifacts, and run traces.

Two ingestion paths

Support automated workflow/API-key uploads and operator-driven dashboard uploads on the same platform.

Database-driven workflows

Define workflows as data, not code. Start from a blank canvas, reusable template, or AI-generated draft without redeploying.

MCP-backed analysis

OCR, descriptions, embeddings, segmentation, similarity search, and retrieval are exposed as MCP tools for workflows and operators.

Persistent analysis corpus

Store source images plus descriptions, OCR, embeddings, segmentations, and derived images for later search and reuse.

Dashboard control plane

Manage projects, workflow keys, service keys, workflows, AI draft generation, uploads, search, chat, and runs from one operating surface.

Run trace visibility

Inspect initial state, per-step deltas, final state, timing, and errors for every workflow execution.

Grounded retrieval and chat

Search by meaning and ask questions against the persisted corpus with source-backed answers.

LayerTechWhat it does
APIBun, Hono, better-auth, Inngest, PinoPresigned uploads, auth, workflow triggers, structured logging
DashboardReact 19, TanStack Router, Tailwind, shadcn/uiWorkflow builder, project/API key management, search, chat, operator UI
AgentsGo, Gin, LangGraph, LangChain, inngestgoGraph loading, workflow execution, step-level run tracking
MCPGo, MCP go-sdk, replicate-go, GORMOCR, descriptions, embeddings, segmentation, similarity search, retrieval tools
StoragePostgres 18 + pgvector, S3-compatible, RedisDocuments, derived artifacts, vector search, sessions, realtime fanout
ClientFlutter, Dart, flutter_gemma, GenUI, fpdartOptional demo client for capture, preview, and GenUI experiments