Your AI Agents Keep Forgetting Context. Ours Don't.
Most AI chat tools are stateless toys. You close the tab, you lose the thread. DCNetwork coordinates 47 specialist agents through a persistent PostgreSQL task board with atomic locking, typed agent mail, and explicit delivery receipts. Your workflows survive restarts. Your data survives reboots.
Deployed on member-owned, EU-sovereign infrastructure — not rented from US hyperscalers.
Why Most AI Tools Fail at Real Work
ChatGPT is great for drafting emails. It's terrible for running your business. Here's why:
No memory
Close the browser tab and your entire operational context vanishes.
No delegation
One agent tries to do everything. It can't. So it hallucinates.
No audit trail
You can't prove what the AI did, when it did it, or why it made that decision.
No integration
It doesn't talk to your CRM, your codebase, or your data warehouse.
In short, it's a chatbot pretending to be infrastructure.
How DCNetwork Actually Works
The orchestration layer is proprietary — built from the ground up, not assembled from third-party AI APIs. Every agent, every tool call, every memory write runs on code we wrote and infrastructure we own.
01
You brief Lucy
You describe what you need in plain English. "Analyze last quarter’s sales data, flag anomalies, and draft a board memo."
02
Lucy delegates
She spawns three specialist agents: a Data Analyst, a Report Writer, and a Fact-Checker. Each gets a specific task, specific tools, and specific constraints.
03
Agents coordinate
They communicate via typed agent mail with explicit delivery receipts. No two agents duplicate work. No task gets lost. Every handoff is logged.
04
You get the result
A board-ready memo with cited sources, anomaly charts, and a confidence score. If something’s wrong, you correct it — and the system learns. Next time, it’s better.
Multi-Agent Coordination
Six interconnected systems enabling autonomous agent collaboration with persistent state and zero race conditions.
Task Board
PostgreSQL FOR UPDATE SKIP LOCKED for atomic task claiming
Eliminates race conditions without distributed locks -- agents claim tasks atomically at the database level.
Agent Group
Dependency-aware parallel execution with 3 strategies
Event-driven dependency release -- agents spawn on completion events, not fixed batch intervals.
Agent Mail
Persistent DB-backed messaging with read receipts
Full PostgreSQL persistence with per-agent read receipts and ephemeral Redis team log for late-joiner context.
Delegation
Typed contracts with single, parallel, and background execution
Depth-scaled timeouts and typed DelegationResult contracts ensure predictable subordinate behavior.
Team Orchestrator
Goal decomposition into 2-6 subtasks with specialist routing
Automatic goal decomposition routes work to the right specialist agent without manual configuration.
Task Queue
Redis-backed priority queue with cron scheduling
Four priority levels (LOW/NORMAL/HIGH/URGENT) with background job loop for stale task recovery.
Signature Capabilities
Chatbots answer and forget. DCNetwork learns, curates its own skills, writes its own knowledge base, chases goals on its own, and puts a council of models on the hard calls.
It learns from every correction — and forgets what stops working.
No thumbs-up needed: regenerate a slide or rerun code and the platform reads it as a signal, clusters repeated fixes into durable DO / AVOID rules, and injects them into future work. Learnings that keep failing are archived automatically, so the knowledge gets sharper — not noisier.
<20% success after 10 uses → auto-archived · 90-day recency decay
A skill library that curates — and rewrites — itself.
New skills are imported and deduped by meaning across the 19,000+ built-in library, then rehabilitated: one model classifies each skill, a different vendor’s model rewrites it to fit the platform. Only high-confidence results apply automatically — the rest wait for a human.
Two-model, cross-vendor review · keep / merge / rehabilitate / retire
A wiki the AI writes about your work — and keeps current.
The platform compiles what it has learned about you into versioned knowledge pages — summary, key principles, common pitfalls, positive patterns — each one traceable to the exact lessons that produced it, and resynthesized as new lessons accumulate.
Self-synthesized · every page sourced to its evidence · auto-refreshed
Give it a goal. It keeps working between your turns until it’s actually done.
A planner breaks the goal into success criteria and a turn budget; after each turn a judge asks “is this done?” — and it’s engineered to never say yes falsely. A “done” verdict can be challenged by an adversarial debate and a second-opinion model from a different vendor before it ships.
Bounded turn + cost budget · you can interrupt anytime
A council of specialist models that debate before they answer.
High-stakes decisions run through a panel of independent models — each on a different tier and vendor — that argue bull versus bear, hold veto power, and get synthesized into one attributed answer. A model from a different vendor re-checks the verdict, so they don’t share blind spots.
5-role council · cross-vendor second opinion · full attribution
Is This Hard Moat Functional Today?
This is not an idealized roadmap or a speculative whitepaper promise. Every single capability listed on this property is running live on our production branch right now.
When you see a metric like 19,000+ built-in skills, that means your active workspace has immediate access to over 19,000 pre-coded, discrete business behaviors — ranging from parsing raw CSV financial tables to cross-checking regional legal statutes. You are not starting from an empty prompt box: you are deploying a workforce that arrives equipped on day one and keeps getting sharper as it learns from your corrections.
Self-Learning Pipeline
A three-tier system that automatically captures, promotes, and consolidates agent knowledge without human intervention.
Implicit Capture
Auto-detects user intent from actions without requiring explicit feedback.
- Slide regeneration signals dissatisfaction
- Code execution failure triggers correction
- Tool retry patterns captured automatically
Learning Promotion
Recurring patterns are promoted to persistent learnings via pgvector semantic clustering.
- Semantic similarity via pgvector embeddings
- Recurrence threshold for promotion
- Auto-prunes patterns with <20% effectiveness
Theme Consolidation
At 30+ learnings, related patterns are consolidated into high-level themes for efficient retrieval.
- Clustering at 30+ learning threshold
- Theme-level knowledge compression
- Self-pruning of ineffective patterns
Knowledge & Retrieval System
One coordinator, 13 context scopes. Hybrid search merges vector + keyword across memories, files, KDS, learnings, corrections, wiki, and project knowledge — deduped and ranked in a single call.
Hybrid Search
Reciprocal Rank Fusion combining vector similarity (70%) and BM25 keyword matching (30%) for optimal retrieval.
13 Unified Context Scopes
One search hits memories, files, KDS, learnings, corrections, wiki, company docs, project notes / errors / summaries — deduped and ranked.
Temporal Decay
Knowledge relevance decays with a 90-day half-life, ensuring recent information is prioritized in search results.
Recency Boost
Documents less than 7 days old receive an additional boost, surfacing the most current knowledge first.
Code-Aware Chunking
Intelligent text chunking that respects code boundaries, function signatures, and document structure for cleaner embeddings.
Context-Aware Embeddings
Embedding generation that incorporates surrounding context and metadata for higher-precision semantic matches.
Agents
Lucy + 38 specialists. Atomic task board, persistent agent mail, 24 starter presets you can clone.
Self-Learning
3-tier capture → cluster → promote pipeline plus a unified search across 13 context scopes.
Marketplace & Spaces
14 Space templates, 10 module entitlements, 19,000+ built-in skills, Markets Pro tiers, Creator OS.
Request Invite + 500 Free COMPUTE Tokens
Platform access is currently invite-only. Request an invite now and get 500 free COMPUTE tokens to test with.
Here's the Deal
DCNetwork is the only AI platform that coordinates 47 specialist agents through a persistent task board with atomic locking, typed agent mail, and a self-learning pipeline that improves from every correction.
Watch a live demo — no signup required
Lucy delegates a 4-agent workflow across research, writing, fact-checking, and formatting — in under 3 minutes.