ABU DHABI – November 01, 2026 -- Context Labs B.V. launched the AI Distillery, a Context Engine that converts an enterprise's operational and business data into a governed, customer-owned Context Package. The package works with any frontier or open-weight model and runs inside the customer's own environment. The product is available now through the Microsoft Marketplace.
Gartner and McKinsey data frame the AI-readiness gap
Gartner predicts organizations will abandon 60% of AI projects unsupported by AI-ready data through 2026. It also expects over 40% of agentic AI projects to be canceled by the end of 2027. McKinsey reports that eight in ten companies cite data limitations as the barrier to scaling AI agents.
Three-step workflow maps data to ontologies and verifies answers
The AI Distillery works in three steps: distill, package and prove. It maps structured and unstructured data to industry-specific ontologies and stores the result in a Context Package with cryptographic provenance. It then checks answers against the company's own records before any model goes into production. Context Labs says this replaces work that has typically required teams of specialist engineers with a guided, governed workflow.
Six design outcomes center on IP ownership and model freedom
Context Labs lists six outcomes for the product:
- Enterprise knowledge stays in a package only the customer controls and is not used to train third-party models.
- Every output carries its data lineage and decision provenance, so answers can be audited.
- The package starts with one facility and extends to others without rebuilding.
- The system runs in the customer's own data center or chosen cloud.
- Customers can switch models without rebuilding the package.
- Verified context reduces the tokens each query uses.
Context Agents and Semantic Context Tunnel deliver traced answers
Context Agents answer operational, commercial and compliance questions from the Context Package, with every figure traced to its source. The Semantic Context Tunnel brings the same context into the AI assistant employees already use. Both operate within access controls the enterprise sets.
"Models come and go. An enterprise's context should not," said Dan Harple, Founder, Chairman and CEO of Context Labs. He argued that frontier models do not supply governance, provenance or trust, and should not absorb the knowledge that makes a company competitive.
ADIPEC 2026 demo targets energy-sector plant records
At ADIPEC 2026, Context Labs is demonstrating a Context Agent that answers operational questions with every figure traced to underlying plant records. The company is at the Arab Development Group stand, Stand #5240, Hall 5, and in the Dell AI Factory with NVIDIA, AI Zone, Hall 13.
Each enterprise license includes an industry starter kit to accelerate time to value.