Cyberhill’s Cerebro now plugs business context into Claude, ChatGPT, Gemini, and Grok

Cyberhill Partners said Cerebro, its enterprise semantic layer, now feeds an organization’s workflows, terminology, and business rules into the enterprise versions of Anthropic’s Claude, OpenAI’s ChatGPT, Google’s Gemini, and xAI’s Grok — so the model reasons over company systems of record with a traceable path, while leaving data in place. The company says the capability is available now.

SOFTWARE desk — same-day primary for a production semantic layer that claims to make multi-vendor enterprise LLMs cheaper, faster, and auditable without moving systems-of-record data.

What Cerebro is, as the same wire has it: a semantic layer — a map of how a company’s words, systems, and rules connect — that sits between enterprise systems of record and the chosen frontier model. Frontier models here means the Claude / ChatGPT / Gemini / Grok class. Cerebro supplies the ontology, relationships, business rules, and lineage that connect an answer to the record behind it, and leaves enterprise data in place. An ontology is a structured map of business terms and how they relate. Lineage means a kept path from the answer back to the exact records used. File that sit-between / leave-data-in-place picture as Cyberhill’s. This desk did not connect a system of record.

How consumption is billed, still company: use is metered in Semantic Reasoning Units, which the company says measure completed reasoning rather than resending raw context on every request. File Semantic Reasoning Units as Cyberhill’s metering name. This desk did not audit a bill.

Cost, speed, and accuracy claims — Cyberhill internal AI Factory testing, not independent Bad Signal benchmarks: the company says sitting between the data and the model so only the context a query needs gets sent cuts token costs by up to 80%. Tokens are the billed chunks of text a model reads or writes. In testing, it says average response time fell from 112.3 seconds to 14.9 seconds. On a 74-question internal set of enterprise business questions, the same underlying model ran twice — once alone, once through Cerebro — and the company reports accuracy rose from 25.7 percent to 93.2 percent and average cost per query fell from $4.89 to $0.98. File those figures as Cyberhill’s internal AI Factory testing. This desk did not rerun the 74 questions.

Traceability, still company: every response retains a reasoning path — sources, hops, constraints, and the exact records used — which the company calls an AI audit trail. The same wire says Cerebro was “born from the US Intelligence Community.” File that path and that line as Cyberhill’s. This desk is not treating that sentence as a classified intelligence-community endorsement, a government certification, or a named agency contract.

Ownership, company: the Cerebro ontology and semantic layer are the organization’s intellectual property, permanently. File that IP claim as Cyberhill’s. This desk did not review a contract.

Named voice on the release: Rob Buller, chief executive officer of Cyberhill. He argues every enterprise has access to the same frontier models, and the advantage is whether the model understands the business and can show its work. File the name and title as his, via Cyberhill. His quotes are color only and stay in Sources.

About-box context, optional and company-attributed: Cyberhill calls itself an advanced AI software development firm serving Fortune 1000 organizations and U.S. government agencies, says it has completed more than 1,000 enterprise software implementations, and says it brings over a decade of enterprise AI experience. Headquartered in Austin, Texas. File those about-box lines as Cyberhill’s. This desk is not inventing named customer logos. None were printed.

Plain English for the rest of the card: semantic layer = a map of how the business’s words, systems, and rules connect so the chatbot does not guess from the open internet. frontier models = the Claude / ChatGPT / Gemini / Grok class. ontology = a structured map of business terms and how they relate. lineage = a kept path from the answer back to the exact records used. Semantic Reasoning Units = Cyberhill’s meter for completed reasoning instead of raw tokens resent each time. systems of record = the official apps that already hold the company’s data.

PRIMARY here: Cyberhill Partners’ 15 Sep 2026 PR Newswire company release — Tier A PRIMARY company source, the original record. The Cerebro for LLMs product page is product-home context, not a second originating newsroom. The Claude / ChatGPT / Gemini / Grok enterprise-context expansion, available-now / stand-up-in-days line, the sit-between systems-of-record picture with data left in place, Semantic Reasoning Units, the up-to-80% token / 112.3s-to-14.9s / 74-question 25.7%-to-93.2% / $4.89-to-$0.98 internal AI Factory figures, the reasoning-path audit trail, the “born from the US Intelligence Community” company line, the ontology-as-customer-IP claim, the Buller title, and the Fortune 1000 / 1,000-implementations / Austin about-box are company-attributed. Speed, cost, and accuracy figures stay Cyberhill internal-test figures — not independently measured here. Product-page-only token-savings percentages and named enterprise-system examples stay off the lead. NOT claimed: named Fortune 1000 customer logos, pricing dollars beyond the company’s internal-test figures, that OpenAI / Anthropic / Google / xAI co-announced this, a classified intelligence-community endorsement, independently verified benchmarks, that this desk tested Cerebro, a stock tip, or investment advice. Distinct from the already-filed g5-labs-14m-seed, cockroach-continuum, wso2-agent-manager-ga, salesforce-koa-nemotron, lectra-apogy, typesafe-ai-40m-seed, and gemini-3-8-live.