Predictive and causal workflows
Use established model-development and evidence workflows instead of starting from individual algorithms.
Embedded Decision Intelligence
Graphite Note can sit behind ERP, CRM, BI, workflow, vertical SaaS and AI-agent products as an embedded predictive, causal and decision layer. Your users stay in your product. The decision intelligence runs behind it.
Where it fits
What you avoid rebuilding
Embedding an existing decision layer can reduce the amount of model infrastructure, validation logic and workflow design a product team has to create and maintain itself.
Use established model-development and evidence workflows instead of starting from individual algorithms.
Carry the context required to explain why a decision was produced and whether approval is needed.
Return structured outputs your existing product can render, route or pass to another service.
Governed agentic decisions
An AI agent can consume a structured decision, but the business rules should stay explicit. Graphite Note can support a policy-bound path from candidate action to evidence, approval and outcome record.
Filter candidate actions through business rules, permissions, customer eligibility and operational constraints before anything can be executed.
Return the expected impact, confidence and supporting evidence so the receiving product or agent does not have to infer why the action exists.
Mark actions for human review, escalation or refusal when evidence is weak, policy is not satisfied or the decision exceeds an agreed authority level.
Commercial models
Graphite Note supports solution-delivery and OEM/API relationships. The practical structure depends on the product, customers, data boundary, deployment model and use case.
This can range from one embedded decision use case to a broader co-developed capability layer.
See partnership modelsExpose decision intelligence through your interface and commercial model.
Combine your domain and distribution with Graphite Note modelling and decision delivery.
Use Graphite Note to operate the analytical layer while your team owns product experience.
Direct answers
No. The purpose of embedded decision intelligence is to let the existing application own the user experience while Graphite Note provides decision outputs behind it.
No. The fit depends more on the value of the use case and the need to add predictive, causal or optimisation capability without building the full stack internally.
An LLM can explain or interact with information. A decision engine is responsible for quantitative prediction, causal evidence, constraints and expected impact. They can work together, but they solve different parts of the system.
Keep policy outside the agent's free-form reasoning. Candidate actions can be checked against eligibility, permissions and operating constraints, then accompanied by evidence and routed to approval or escalation when required. The agent consumes the governed result rather than inventing the policy itself.
Start with one embedded use case and a clear API boundary.