Cyberhill Introduces Cerebro for LLMs: A Unified Semantic Layer Powering All Frontier Models
Cerebro is the semantic layer for all frontier LLMs, mapping an organization's workflows, terminology, and business rules to the model of choice, with traceability, lower cost, and faster response times.
AUSTIN, Texas, Sept. 15, 2026 /PRNewswire/ -- Cyberhill Partners, Inc., a leader in advanced enterprise AI software development, today announced that Cerebro now delivers full business context to the enterprise versions of Anthropic's Claude, OpenAI's ChatGPT, Google's Gemini, and xAI's Grok. The capability is available now, and an organization can stand up the business context a chosen model needs in days.
"Every enterprise has access to the same frontier models. The advantage is not the model, it is whether the model understands your business and can show its work," said Rob Buller, Chief Executive Officer of Cyberhill. "Cerebro gives an organization that understanding out of the box, across whichever model it has already chosen. It's a game-changer for enterprise AI, and Cerebro is at the literal heart of that change."
Enterprise data sits across dozens of systems and business units, the same concept carries a different name in each, and the rules that govern the work exist mostly as institutional knowledge. Cerebro works with the model an organization has already chosen, supplying the ontology, relationships, business rules, and lineage that connect an answer to the record behind it, with enterprise data left in place. Consumption is metered in Semantic Reasoning Units, which measure completed reasoning rather than raw context resent on every request.
Key capabilities of Cerebro for frontier LLMs include:
- Lower Cost: LLMs alone consume large volumes of tokens per query, and the more complex the question, the more expensive it gets. Cerebro sits between the data and the model, so only the context a query needs gets sent. That cuts token costs by up to 80%.
- Business Context: Cerebro is a truth engine for LLMs. It connects to the systems of record and builds an ontology of the business terms and rules, so the model reasons over the organization's own operations rather than general knowledge from the internet.
- Traceability: Every response retains a reasoning path: sources, hops, constraints, and the exact records used. This serves as the first AI Audit Trail. Born from the US Intelligence Community, Cerebro delivers answers that are accurate and defensible. LLMs alone cannot do that.
- Speed: Cerebro gives the model only the context each request needs rather than resending broad material on every call. In testing, average response time fell from 112.3 seconds to 14.9.
- AI Intellectual Property Ownership: The Cerebro ontology and semantic layer are the organization's intellectual property, permanently.
In Cyberhill's internal AI Factory testing, the same underlying model answered a 74-question set of enterprise business questions twice: once on its own, and once reasoning through Cerebro's semantic layer. No other variable changed between the two runs. Accuracy rose from 25.7 percent to 93.2 percent, and average cost per query fell from $4.89 to $0.98.
Organizations standardizing on a frontier model can connect it to their own business context at cyberhill.ai/cerebro/llms.
About Cyberhill
Cyberhill is an advanced AI software development firm serving Fortune 1000 organizations and U.S. government agencies. The firm has completed more than 1,000 enterprise software implementations and brings over a decade of enterprise AI experience. Cyberhill serves organizations across all industries seeking a faster, lower-risk path to production-grade, highly scalable enterprise AI. Headquartered in Austin, TX.
Media Contact:
Carolyn Hassan, VP of Marketing
Cyberhill Partners
www.cyberhill.ai | [email protected]
SOURCE Cyberhill Partners, Inc.
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