Noetis Supply Chain · Business engine
Supply Chain Risk Analysis Engine
Assesses disruption exposure from supplier and inventory data.
Answers: "Can an engine assess disruption exposure from our supplier data?" For supply chain planners.
Works on supplied snapshots only. It has no live supplier, shipping or news feeds.
Available today
ImplementedImplemented: runs on the shared runtime with supplied material. One bounded development check on 2026-10-12 took 127.8s with 15 model calls and ended "incomplete". That is a development signal, not an evaluation. Customer access is by approved account.
What you send
- Question
- Supplied text material
- Text material up to 150,000 characters per run
What comes back
- Exposure assessment and mitigation options.
- Findings with the located quote and a support status from claim review
- Release status: released, incomplete with reasons, or failed
- Executed roles, usage and measured cost
Sample
Authored illustration. Written by Encevra to show the workflow. Not customer data and not a recorded model output.
How exposed are we to a disruption at our single resin supplier?
Supplier X supplies 100% of resin, lead time 6 weeks. Stock on hand: 3 weeks. Weekly use 20 tonnes. Alternate supplier Y quoted 10 weeks to qualify. Port strike notice for X's region next month.
- Single source dependencies named from the supplied records
- Exposure linked to stated lead times and stock levels
- Mitigations to evaluate, with data age noted
The real response shape is documented in the API reference.
How the workflow operates
Each role is a responsibility in the workflow, served by a third party language model. More roles are not automatically better; depth and routing decide which run.
Built with
Models this engine uses: OpenAI (GPT), Anthropic (Claude). Specialists run on OpenAI models and the claim review and final brief on Anthropic models. If a provider has a temporary failure, the step can fall back to an OpenAI model, and the run records that.
Network Mapper
Map suppliers, facilities and dependencies.
Demand and Inventory Analyst
Examine demand assumptions and stock positions.
Lead Time Analyst
Check timing variability and constraints.
Disruption Analyst
Model explicit disruption scenarios.
Mitigation Planner
Compare resilience measures and costs.
Evidence and deployment
Evidence
This engine reads the text you send in the request. Each released finding carries the exact quote and its character span in that text, located mechanically before release. Quotes that cannot be located are labelled Insufficient evidence and never shown as source verified. Interpretation is reviewed as a separate step, and gaps such as a missing clause describe what was searched instead of citing text that is not there.
Deployment
Runs on Encevra hosted infrastructure using the third party models listed above. Every model call and fallback is checked against the deployment policy first. Private cloud and air-gapped deployment are planned; discuss deployment requirements.
What it does not handle
- Placing orders
- Forecasts without supplied data
- Spreadsheet and dataset execution is not available: Not built.
- Uses only supplied material. No freshness guarantee beyond the documents provided.
- Required for every output during trials.
How to integrate
Send "engine": "supply-chain" with your question and material from your server. Keys stay server side.
How to evaluate it
No published result for this workflow yet. Build a small answer key from your own work and compare against a strong single model baseline. See the evaluation checklist and method.
Cost and rights: pricing and licensing. Showing outputs to your own customers needs a written agreement.
Related engines
Content reviewed 2026-10-12 by the Encevra engine team. Engine version 0.1.0 on noetis-core-1.