HLA-Compass

AI that understands immunopeptidomics.

Ask a question. The copilot queries proprietary HLA data, picks the right MCP tool, and runs a governed analysis — so you can discover neoantigens in minutes, not months.

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0K+HLA peptides

0+MCP tools

0+LLM providers

0%Audit coverage

How it works

From question to governed answer in three steps

Step 1

Ask in natural language

Describe your research question — the copilot understands immunopeptidomics terminology, your data context, and available tools.

Step 2

AI selects and chains tools

The copilot reads MCP descriptors from the tool marketplace, selects the right analytical module, configures inputs, and plans the execution.

Step 3

Governed execution with audit trail

Every action is logged, budget-controlled, and traceable. You get results with full provenance — which data, which tool, which model.

AI Copilot

Ask a question. Get a governed answer.

The copilot reads your question, queries proprietary data, selects the right MCP tool, and runs a governed analysis — with full audit trail.

HLA-Compass AI Copilot

Which peptides from KRAS G12D are presented on HLA-A*02:01 in our lung tissue dataset?

I will query the ligandome for KRAS G12D neoepitopes restricted to HLA-A*02:01, then filter against your lung tissue samples.

MCP Tool: ligandome-query

source: lung_tissue_batch_04 · allele: A*02:01 · gene: KRAS · mutation: G12D

3 peptides found · 2 above presentation threshold

Found 3 peptides from KRAS G12D on HLA-A*02:01. Two pass the presentation threshold with high confidence (q-value < 0.01).

GovernedAudit: #LQ-28470.3 ACT

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Why this AI is different

Most AI tools hallucinate on domain questions. HLA-Compass is grounded in proprietary data, governed by design, and built for pharma.

AI-native architecture

MCP-ready analytical tools the copilot discovers and chains autonomously. Agentic execution with full reasoning traces.

Grounded in real data

Proprietary HLA ligandome from real human tissue — 50K+ peptides the AI can query, not general-purpose predictions.

Enterprise governance

Immutable audit trail, row-level data isolation, credit-based billing, and supply chain attestation on every module.

HLA-Compass vs. building in-house

What it takes to replicate the platform internally.

Feature	HLA-Compass	In-house
Curated HLA ligandome
MCP-ready analytical tools
AI copilot (multi-model)
Governed agentic execution
Row-level data isolation		Partial
Credit-based billing
Immutable audit trail		Partial
Module marketplace
Python SDK + CLI		Partial
Supply chain attestation
Time to first analysis	Days	Months

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