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Kora Reliable agentic workflows MXCP Enterprise-grade MCP framework
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From manual work to AI-run operations.

We help companies adapt to AI without starting over, building on the data and systems they already run.

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Our mission

The shift to AI, done responsibly.

AI is reshaping every industry, and companies have to adapt with it. We help them make that shift on their own terms, with systems that operate reliably in production, comply with the laws they're held to, and produce the proof when an audit comes.

The same desk on a bright morning, tidy, with the analyst supervising an AI interface that reads documents and flags one step for approval To
An analyst working late at a desk buried in paper files and printed spreadsheets From

From

Manual work, hidden mistakes.

Data retyped between spreadsheets, inboxes, and old systems. Slow, exhausting, and every handoff is a new chance for an error.

To

AI does the work. Your team stays in charge.

Routine steps run on their own, exceptions reach the right person, and every approval is recorded.

What we engineer

Four layers behind reliable AI.

Below every dependable AI system, the same four engineering problems have to be solved properly.

Data

Clean, governed, queryable. We connect to the systems where enterprise knowledge already lives - without forklift migrations or shadow copies.

Integration

AI talks to existing systems the way enterprises require: typed, traced, permissioned, idempotent. Every call accountable.

Governance

Policy as code, not slideware. Access, audit, lineage, and review enforced at the system level - not the trust-the-developer level.

Runtime

Observable, recoverable, predictable behavior under production load. Failure modes you can detect, debug, and design around.

Uptime 99.99% · P99 142ms · Err 0.003% · Status Nominal

Products

Built because enterprises needed them.

Both products emerged from real production engagements - the same architectural problems showing up again and again. We hardened the solutions into infrastructure anyone running enterprise AI can use.

Kora

Reliable agentic workflows

Production-grade orchestration for AI agents. Built so they behave the same way on the thousandth run as on the first - typed inputs, traced calls, deterministic recovery.

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MXCP

Enterprise-grade MCP framework

Open-source framework for putting Model Context Protocol servers into production: typed schemas, policy enforcement, observability, and operational guardrails out of the box.

mxcp.dev

Endorsements

“RAW is the one partner to get all company data available for enterprise AI. Securely. Continuously. Effortlessly.”

Dorian Selz
Dorian Selz Squirro

Writing

Engineering AI, in depth.

Long-form writing on the architectural decisions, failure modes, and trade-offs behind production AI - from the engineers who've been building enterprise systems since 2015.

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FAQ

Questions, briefly answered.

What does RAW Labs do?
RAW Labs helps companies move from manual work to AI-run operations. We connect AI to the data and systems a company already runs, so routine steps run on their own while people stay in charge of approvals and exceptions. Founded in Switzerland in 2015, we spent a decade in enterprise data engineering and now build the data, integration, governance, and runtime layers AI needs to operate reliably, comply with regulation, and produce audit-ready evidence. We serve enterprise customers globally.
Who is RAW Labs for?
Platform-engineering teams putting AI infrastructure into production, application developers building domain-specific agents, security and compliance teams that need provable audit trails, and OEM partners embedding governed AI capabilities inside their own products. The common thread is enterprises moving from manual processes to AI-run operations under regulatory pressure.
What industries does RAW Labs work with?
Telecommunications, manufacturing, financial services, and healthcare. Since 2015 we have shipped high-performance data virtualization, data lakes, advanced analytics, and secure data access across each of those industries. The same engineering discipline now applies to AI infrastructure for those same regulated sectors.
Is RAW Labs a consulting firm or a product company?
Both, deliberately. We engineer custom infrastructure for clients in code - not slides - and we ship two products of our own: Kora (production-grade agent orchestration) and MXCP (open-source Model Context Protocol server for governed data access). Most engagements use the products as the foundation and add custom engineering on top.
How does RAW Labs handle security and compliance?
Security is foundational, not bolted on afterwards. Across every engagement and product, access is controlled at each layer, actions are checked against policy before they run, and a complete, audit-ready record is produced automatically. The guiding model is zero-trust: nothing is assumed safe by default, every request has to be explicitly authorised, and sensitive data stays protected throughout.
How do I engage RAW Labs?
Talk to us. We’ll discuss your stack, deployment model, and regulatory constraints, then recommend the right combination of engineering work and our products. Typical enterprise engagements move from first conversation to a production-ready deployment - with full authentication, policies, and observability - in 2-4 weeks. Reach the team at https://raw-labs.com/contact.

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Get AI into your production.

Bring us the system you're trying to ship. We engineer the data, integration, governance, and runtime layers behind it - so your AI runs reliably, audits cleanly, and stays under your control.

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