Andes Labs

Structured knowledge
for AI agents.

The knowledge graph that turns conversations into connected intelligence. Local-first. MCP protocol. Open source.

The Godfather, mapped as a knowledge graph

Graph Intelligence

Ask questions that search can't answer.

Vector search finds documents. Kernal traverses relationships.

kernal query

Who had motive to betray the Corleone family?

1
Carlo RizziBetrayalEmilio Barzini

Secret alliance with rival family

2
Carlo RizziSetupSonny Corleone

Orchestrated the ambush at the causeway

3
Salvatore TessioBetrayalEmilio Barzini

Arranged meeting as a trap for Michael

Kernal traverses relationships to surface patterns invisible to keyword search. The graph knows who connects to whom — and why.

Now imagine this is your
client portfolio.

Fifty meetings. A hundred and ninety people. Fifteen hundred relationships. Every name, every connection, every promise your team has ever made — structured and queryable by your AI agent.

50+

Transcripts processed

190+

People extracted

1,500+

Relationships mapped

8

Enterprise accounts

Real production data from enterprise consulting engagements.

Philosophy

“An agent without context is a chatbot.
An agent with context is an employee.”

AI models get better every quarter. But a better model without your context still can't answer “Who introduced Sarah to the Hydro project and what was their concern about the timeline?”

Context is the durable layer. The thing that makes AI useful in professional services isn't the model — it's the structured knowledge the model can reason over. Better models make Kernal more valuable, not less.

If a product's value can be rendered obsolete by a better version of Claude or GPT, it lacks a structural moat. Kernal passes this test. The graph deepens with every conversation, and no model can replace what it contains.

Data Sovereignty

Your graph. Your machine. Your models.

Most AI knowledge tools send your data to someone else's servers. Kernal doesn't. No DPA needed. No data residency concerns. No vendor training on your client intelligence.

Local processing

Entity extraction runs via Gemma 4 on your machine. Your transcripts, client names, and deal details never leave your infrastructure.

Local storage

Your knowledge graph lives in a SQLite file on your device. No cloud database. No vendor access. Full portability.

Open protocol

MCP is an open standard, not a proprietary API. Connect Kernal to Claude, Cursor, or any compatible tool. No vendor lock-in.

Executive searchConsultingLaw firmsRegulated industries

Architecture

Five layers of intelligence.

Every entity connects to every other via the relationship graph. The graph is the product.

IntentGoals and milestones
e.g. “Go legitimate within 5 years
CommercialDeals, pipeline, stakeholders
e.g. “Las Vegas Casino Acquisition
IntelligenceStrategic plans, patterns, insights
e.g. “Barzini is the real threat, not Tattaglia
ExecutionActions, tasks, decisions
e.g. “Send Clemenza to handle the Vegas situation
ConversationMeetings, calls, transcripts
e.g. “Peace Summit with the Five Families

Capabilities

What Kernal does.

Entity Extraction

Drop in a transcript. Kernal extracts people, organizations, topics, and the relationships between them. No templates. No configuration. Just structure.

Graph Search

Not just keyword matching. Query across relationships: 'Who at Nordic Tech has influence over the SAP decision?' Kernal traverses the graph.

MCP Protocol

Plug Kernal into Claude, Cursor, or any MCP-compatible tool. Your agent gets structured context about your world — people, relationships, history — in every conversation.

Meeting Prep

Before any call, Kernal surfaces: who you're meeting, their org chart position, recent interactions, open action items, and strategic context. Automatically.

Built For

Professional services that
run on relationships.

Kernal is designed for people whose work depends on knowing who connects to whom, what was said, and what it means.

Executive Search

Map candidate networks, board relationships, and organisational dynamics. Know who knows who before the first call.

Management Consulting

Build institutional memory across engagements. Every meeting, every stakeholder, every strategic decision — structured and searchable.

Strategic Advisory

Track deal pipelines, stakeholder influence, and client goals across your portfolio. Your AI agent knows the full picture.

Law Firms

Matter context that compounds. Client relationships, precedent connections, and engagement history — locally stored, never shared.

Get Started

Three commands. That's it.

1

Install

npx @kernal/mcp
2

Connect to Claude

Add Kernal as an MCP server in Claude Desktop or Claude Code.

3

Talk naturally

Start having conversations. Kernal extracts and connects entities automatically.

Community

Join the builders.

💬

Discord

Ask questions, share what you’re building, get help.

Join Discord
🐙

GitHub

Star the repo, open issues, contribute.

View Repo
📝

SubStack

Technical deep dives on agent architecture.

Coming Soon

Build agents that remember.

See how Kernal works with your data. Book a 30-minute demo or start building with the open-source core.

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