WeaverAI One is a private AI platform that gives your whole organization Copilot-like capabilities — but you pay for actual usage, keep data in your own environment, and choose any model. No per-user licensing. No vendor lock-in.
Azure AI Foundry · Bedrock · Gemini · OpenAI · Local
Vector DB · RAG · Docs · Connectors
Trusted by regulated, data-sensitive organizations — where AI can't mean handing data to someone else's cloud.
Copilot is great inside Office. WeaverAI One governs AI across your entire organization — with usage-based cost, data control, model choice, agents, and RAG.
| Capability | Microsoft 365 Copilot | WeaverAI One |
|---|---|---|
| Pricing model | Per-user subscription — pay for every seat | Usage-based consumption + platform license — pay for what you use |
| Model choice | Microsoft ecosystem only | Azure AI Foundry, Bedrock, Gemini, OpenAI, local models |
| Data control | Processed in Microsoft cloud | Stays in your environment |
| Deployment | SaaS only | On-prem, private cloud, or hybrid |
| RAG | Microsoft Graph–centric | Enterprise knowledge base, vector DB, custom connectors |
| Agents | Microsoft Copilot agents | Private enterprise agents and workflows |
| Observability | Microsoft admin tools | LangFuse tracing, cost attribution, token tracking |
| Vendor dependency | High dependency on Microsoft ecosystem | Choose model providers per organizational policy |
WeaverAI One doesn't replace Copilot inside Office apps — it gives your whole organization a private, flexible AI layer with data control, model choice, agents, RAG, automation, and cost control.
An organization with 500 employees buys 500 Copilot seats. But only ~150 use AI daily. You're paying for 350 idle licenses — every month. WeaverAI One bills the 150 active users' actual consumption instead. As adoption grows, cost scales with real value delivered — not headcount.
From your users, through the gateway, to your models and your data — every request passes a governance layer (DLP, SSO, policy, audit) and an observability layer (logs, metrics, traces, costs). Nothing leaves your perimeter unseen.
Connect every model provider, define usage policies, track tokens and costs, and decide which information can be sent to which model.
Track and cap AI spending by team, application, model, and workload — and see it before the bill arrives.
Apply masking, filtering, and governance before sending data to external model APIs.
Connect Azure AI Foundry, Amazon Bedrock, Gemini API, OpenAI, and self-hosted models.
Use policy-based routing to select the right model for each task.
Use cloud models for advanced reasoning and local models for private or regulated workloads.
Trace every request, response, user, model, and cost through the observability layer.
WeaverAI One is built for healthcare, finance, insurance, government, defense, and manufacturing — anywhere AI capability can't come at the cost of control over your information assets.
Deploy a private AI platform that gives your organization Copilot-like capabilities, model freedom, and full control over data and cost.