scopefunc=lambda: id(gevent.getcurrent())"
Heuristic Learning via MCP
Heuristic Learning as a Service
Your AI learns how things are done — procedures, workflows, domain expertise. Plugs into ChatGPT, Claude, Cursor, and any MCP client. No setup required.
ChatGPT
Claude
Cursor
Cline
Any MCP
Multi-Dimensional Intelligence
Not just keywords. Your AI matches what you're looking for AND what task you're doing.
Content
What the knowledge is about
Useful For
What task it helps with
Systems
Technologies involved
Tasks
Operations being performed
More Than Memory
Most agent memory is one of two shapes: text dumped into a vector store, hoping the right chunk comes back — or a folder of markdown files the agent has to read back in. Ours is a system — shaped to your domain, tuned against ground truth, and built to prove what it knows.
Custom Schemas
Shape memory to your domain. Define your own embedding dimensions — each its own searchable space — plus exact-match fields for IDs and codes.
Tuned Retrieval Weights
Ranking that’s measured, not guessed. Per-dimension weights are calibrated against ground truth — matching what a fact is useful for, not just what it says.
Automatic Temporal Consistency
Knowledge that stays current. Time-bound claims are caught at write time, retrieval is time-aware, and superseded facts are corrected or retired — so yesterday’s answer never resurfaces as today’s.
Self-Improving Recall
Memory that grades itself. A weekly eval harness re-scores every stored fact and flags anything that regressed or fell out of reach.
Mesh Delivery
A live fabric between agents. They share learnings into one bank, message each other directly, and the mesh flags overlapping work in real time — so the fleet compounds instead of colliding or starting from zero.
Proactive Delivery
Context that arrives unprompted. Agent hooks surface the right prior knowledge as work happens — pushed to where the agent is, not waiting to be queried.
Honest Write Receipts
Know it actually landed. Every write returns a receipt you can verify — stored and searchable, not just “queued.”
Semantic Dedup & Edit-in-Place
No duplicates, ever. New facts merge, update, or flag conflicts — and any entry can be inspected, edited, or removed with a full audit trail.
4,871
deliverables shipped by our own agent fleet
in the last 90 days — median scope under an hour, every one audit-trailed
in the last 90 days — median scope under an hour, every one audit-trailed
5 Minute Setup
OAuth Protected
Connect Your Way
MCP config, web UI, or direct API. Your data stays encrypted.
1
Create a Knowledge Bank30 sec
2
Copy the Config30 sec
3
Start LearningAutomatic
Also Connect Via
ChatGPT Web
Claude.ai
REST API
.mcp.json
// Add to any MCP-compatible client
{
"mcpServers": {
"my-knowledge-bank": {
"type": "http",
"url": "https://www.gurucloudai.com/mcp/YOUR_ID/mcp"
}
}
}
{
"mcpServers": {
"my-knowledge-bank": {
"type": "http",
"url": "https://www.gurucloudai.com/mcp/YOUR_ID/mcp"
}
}
}
SOC 2 Ready
End-to-End Encrypted
Your Data, Your Control
Heuristic Learning via MCP
Plugs into ChatGPT, Claude, Cursor. Free to start.
Get Started Free The Architecture
How It Works
AI agents report learnings. AI agents query for context. An intelligent layer keeps everything organized and relevant.
Reporting
Reporting Agent
AI discovers & reports knowledge
Knowledge Entry
Multi-dimensional data
Processing Agent
Validates, dedupes, enriches
Semantic Dedup
No duplicates, ever
Knowledge Bank
Vector embeddings
Content
Useful For
Systems
Tasks
Querying
Ranked Results
Best matches returned
Reranking Agent
Scores & prioritizes
Multi-Dim Search
4 parallel queries
Querying Agent
AI requests context
Click any node for details and examples
Real Example
Here's an actual knowledge entry and how it gets retrieved through multi-dimensional search.
Stored Entry
"When using gevent with SQLAlchemy's scoped_session, provide a custom scopefunc for session isolation. Use
Useful for: Configuring SQLAlchemy sessions with gevent
SQLAlchemy
gevent
database
~/project
$ claude "set up database connection pooling"
# AI queries Knowledge Bank with 4 dimensions:
content_query: "database connection pooling"
useful_for_query: "setting up database connections"
relevant_systems_query: "database, pooling"
relevant_tasks_query: "configuration, setup"
Found 2 relevant heuristics:
1. "Use scoped_session with gevent scopefunc..."
useful_for: configuring SQLAlchemy
match: content + useful_for + systems ↑ boosted
2. "Pool size should match worker count..."
useful_for: production database setup
# AI queries Knowledge Bank with 4 dimensions:
content_query: "database connection pooling"
useful_for_query: "setting up database connections"
relevant_systems_query: "database, pooling"
relevant_tasks_query: "configuration, setup"
Found 2 relevant heuristics:
1. "Use scoped_session with gevent scopefunc..."
useful_for: configuring SQLAlchemy
match: content + useful_for + systems ↑ boosted
2. "Pool size should match worker count..."
useful_for: production database setup
Ready to Start Learning?
Set up in 5 minutes. Free to start.
Get Started Free Built for Development Teams
Your Codebase
Learns With You
AI that remembers your git conventions, testing requirements, and architectural decisions. Shared across your entire team. Works with Claude Code, Cursor, Cline, and more.
~/my-project
$ claude "add user authentication"
# AI queries Knowledge Bank with:
# content_query: "user authentication implementation"
# useful_for: "adding authentication to routes"
Found 4 relevant heuristics:
git: "Branch naming: feature/TICKET-description"
arch: "Use JWT tokens per ADR-012, never sessions"
test: "Auth routes need 401 + success test cases"
gotcha: "Always rate-limit authentication endpoints"
# AI writes code following YOUR team's practices
# AI queries Knowledge Bank with:
# content_query: "user authentication implementation"
# useful_for: "adding authentication to routes"
Found 4 relevant heuristics:
git: "Branch naming: feature/TICKET-description"
arch: "Use JWT tokens per ADR-012, never sessions"
test: "Auth routes need 401 + success test cases"
gotcha: "Always rate-limit authentication endpoints"
# AI writes code following YOUR team's practices
What Gets Learned
Captured automatically. Shared across the team.
Git Conventions
Branch naming, commit formats, PR requirements, merge strategies.
Testing Practices
Coverage requirements, mocking patterns, integration test setup.
Architecture Decisions
Design patterns, database conventions, API standards with context.
Gotchas & Pitfalls
"Never do X because Y" — captured when discovered, never repeated.
Database Patterns
Session management, connection pooling, transaction handling.
Team Preferences
Code style, review feedback patterns, design philosophies.
Beyond Just Reading Code
| AI Reading Code | Knowledge Bank | |
|---|---|---|
| Git conventions | Infers from history | Explicitly knows rules |
| "Don't do X" | Can't know what's NOT there | Captures anti-patterns |
| Why decisions were made | Lost to time | Preserved with context |
| Cross-repo knowledge | Isolated per project | Shared across all |
5 Minute Setup. Lifetime of Learning.
Add one config file. Your AI starts learning immediately.
Get Started Free For Teams & Enterprise
Institutional Knowledge That Scales
Capture how your organization works — procedures, workflows, domain expertise. New hires inherit years of knowledge from day one.
How It Works in Practice
1
Sarah in Accounting teaches the AI: "When we get international invoices, always convert to USD using the rate from our treasury report."
2
New hire Mike asks AI about processing an international invoice. AI already knows the procedure — guides him perfectly.
3
Every department contributes. Knowledge compounds. AI becomes your organization's collective brain.
Captured Procedure
"International invoices: 1) Verify vendor in approved list, 2) Convert using treasury FX rate from daily report, 3) Route to regional manager. Amounts over $50k need CFO approval."
Useful for: Processing international invoices, accounts payable workflow
Transform Your Operations
Every employee interaction makes your organization smarter.
Procedural Learning
Capture how things are done — not just facts. Workflows, approval chains, business logic.
Cross-Team Intelligence
Knowledge from sales helps support. HR insights reach managers. Everyone benefits.
Instant Onboarding
New hires inherit years of institutional knowledge from day one.
Knowledge Preservation
When people leave, their expertise stays. No more tribal knowledge loss.
Self-Updating
AI-powered deduplication and consistency. Zero manual curation required.
Works Everywhere
Plugs into ChatGPT, Claude, Cursor — any MCP-compatible AI your team uses.
Turn Tribal Knowledge Into Team Intelligence
Works with any MCP client. Free to start.
Get Started Free