Gives intelligence context
Built once. Reused across every AI use case where it applies.
Core is Bristlecone's Shared Intelligence Layer: a reusable layer of business context, semantics, memory, evidence, and policy that helps AI understand, reason, and act consistently across the enterprise.
The quiet problem behind many AI efforts
A customer, material, location, order, shipment, supplier, metric, or policy can be represented differently across systems and functions. People work around it because they know the history. AI doesn't.
As companies add narrow agents, each one ends up rebuilding the same context, mappings, reasoning, and governance. That's slow, expensive, and a recipe for inconsistent answers.
What Core does
Core consolidates that repeated intelligence into a shared cognitive runtime: common cognitive layers plus a canonical business ontology, so:
- Relevant context carries across agents and workflows.
- Decisions stay connected to evidence and provenance.
- Actions stay within customer-defined guardrails.
It does this through:
- Shared definitions, relationships, and domain semantics.
- Knowledge structures and metadata.
- Trusted context from operational and external data.
- Reusable knowledge for analytics, agents, and applications.
- Governance, lineage, quality, and access controls.
Why it matters economically
By avoiding repeated context rebuilding, reasoning logic, data remapping, and governance agent by agent, Core reduces duplicate work and lowers compute and maintenance costs, while improving consistency, explainability, and control. It's model-neutral and cloud-neutral, so shared intelligence works across environments without tying the architecture to a single LLM or cloud.
How value shows up
We measure reuse of shared definitions, less reconciliation work, answer consistency, traceability, faster onboarding of new use cases, better retrieval quality, and fewer context-related errors.
Where Core fits
Core supports Vantage, Amplify, Arc-enabled software delivery, and intelligent products with shared, governed business context. It can be used alongside data platforms such as Snowflake and Databricks.
What leaders ask about Core
Practical answers to the questions that often shape the first conversation.
How does Core keep supply-chain measures and entities consistent across planning, analytics, and AI?+
Core connects shared definitions and relationships for entities such as products, suppliers, orders, inventory, service, and performance measures. That gives planning models, reports, applications, and agents a reusable interpretation of the same business context, with lineage and policy attached.
How is Core different from a data warehouse?+
A data warehouse stores and organizes data. Core sits above the data and organizes meaning: definitions, relationships, context, evidence, and policies that analytics and AI can reuse.
Why do AI agents need shared context?+
Without it, each agent has to learn separately what the business's data means, which leads to duplicated work and inconsistent answers. Shared context makes every agent faster to build and more reliable.