The Vottre AI Platform

AI that maps your operations, then tells you what to do about it.

Vottre builds a living, multi-tier graph of your suppliers, trade flows, and emissions, runs machine learning across it continuously, and puts AI agents on top that explain what changed and where to act. One platform, three pillars, no new system of record.

Tiers mapped

n-tier

Monitoring

Continuous

Output

Explainable

How the platform works

Four layers, one pipeline. Raw operational data goes in; a reasoned, auditable view of risk and carbon comes out.

Data layer

Connectors pull from your ERP, procurement, logistics, and GTM systems - trade determination, logistics execution, and customs brokerage - plus public filings, sanctions lists, trade records, weather, and emissions factor libraries.

Network graph

Entity resolution and NLP link millions of records into a multi-tier graph of suppliers, sites, products, and shipments - including the tier-2 and tier-3 relationships you never contracted with.

Model layer

Machine learning scores resilience, financial, cyber, compliance, and ESG risk, and estimates product and shipment emissions where primary data is missing - with confidence bands, not false precision.

Agent layer

AI agents monitor the graph continuously, explain what changed in plain language, draft supplier outreach, and route alerts to the team that owns the decision.

What the AI actually does

Specific jobs, specific methods. Here is where models do the work that people cannot do at this volume or speed.

Entity resolution at scale

The same supplier appears five ways across your systems. Models reconcile names, addresses, tax IDs, and ownership into one canonical entity so risk and carbon aggregate correctly.

Event detection

Language models read news, filings, port notices, and regulatory feeds in dozens of languages, and flag only the events that touch your graph.

Predictive risk scoring

Models learn from historical disruption patterns to rank which suppliers, lanes, and sites are most likely to fail next quarter - and what it would cost you.

Emissions estimation

Where primary supplier data is missing, models infer product and shipment footprints from spend, material mix, mode, and distance, then improve estimates as real data arrives.

Scenario simulation

Ask what happens if a port closes, a tariff shifts, or you re-source a category. The graph re-runs and returns the resilience and carbon consequences side by side.

Explainable output

Every score and estimate carries its inputs, methodology, and lineage. Auditors, assurance providers, and your own analysts can trace any number back to source.

Three agents, three pillars

Each agent owns a pillar, works the same graph, and hands off to the others when a signal crosses domains - a sanctioned supplier is also a carbon problem.

See the network

Network agent

Watches multi-tier supplier structure. Surfaces new concentration, single points of failure, and ownership changes as they appear.

Trust the flows

Trade agent

Reads classification, sanctions, and duty exposure across shipments. Flags declarations likely to fail before they are filed.

Own the footprint

Carbon agent

Tracks emissions against targets across sites, products, and shipments. Explains variance and proposes the highest-leverage reductions.

How we build it

An intelligence layer, not a rip-and-replace

Vottre sits above your existing GTM, ERP, and sustainability tools. Your systems of record stay where they are; Vottre supplies the reasoning across them.

Models where they earn their place

Deterministic rules run compliance logic. Machine learning handles pattern detection and estimation. Language models handle unstructured text. No model is used for work a lookup can do.

Your data stays yours

Customer data is never used to train shared models. Tenancy is isolated, access is role-scoped, and every inference is logged for review.