Enterprise AI Platform
One governed foundation for building, deploying, and scaling AI across a large organization. Workisy centralizes identity, model management, data connectors, policy guardrails, and audit logging so every team ships on approved infrastructure instead of assembling its own.
Features
Powerful Capabilities, Built for Scale
Every tool you need to run a world-class operation, from day one to enterprise scale.
Identity and Access Control
Single sign-on through your existing identity provider, with roles and groups synchronized automatically. Permissions govern who may invoke which application, reach which data source, and change which configuration.
Model Management
Register commercial and open-weight models behind one internal gateway, then promote or retire versions centrally. Applications reference a logical model name, so a provider change never requires touching application code.
Governed Data Connectors
Managed connectors index content from document stores, databases, and line-of-business systems on a schedule you control. Source-system permissions are preserved at query time so retrieval never widens a user's existing access.
Policy Guardrails
Central policies screen prompts and responses for sensitive data, restricted topics, and prohibited use before anything reaches a user. Rules are defined once by the governance team and enforced across every application on the platform.
Full Request Audit
Every invocation is recorded with the requesting identity, the application, the model version, the sources consulted, and the policy verdict. Auditors get an evidence trail that reconstructs any individual decision months later.
Central Application Registry
Each assistant, agent, and automation running in the business is catalogued with its owner, data scope, and approval status. Leadership finally has one accurate answer to what AI is running and who is accountable for it.
Consumption and Cost Controls
Usage is metered per team, application, and model, with quotas and alerts that stop runaway spend before an invoice arrives. Chargeback reports let finance allocate cost to the business units generating it.
Deployment and Residency Options
Run in the Workisy cloud, in your own cloud tenancy, or in a private region where data must remain inside a jurisdiction. The platform's capabilities and administration are identical across every deployment mode.
How It Works
Up and Running in Three Simple Steps
Establish the Foundation
Connect identity, choose a deployment mode, register approved models, and encode your organization's data-handling and acceptable-use policies as enforceable platform rules.
Onboard Teams and Applications
Business units build assistants, agents, and automations on shared connectors and approved models, each registered with a named owner and a defined data scope before it goes live.
Operate and Scale
Administrators monitor quality, spend, and policy events from one console, promoting proven applications across the enterprise while retiring the ones that stopped earning their keep.
A closer look at the Workisy enterprise AI platform
Why scattered AI pilots stall before they reach production
Enterprises rarely struggle to start with AI. They struggle at the moment a promising pilot meets security review, procurement, and the question of who is accountable when an answer is wrong. Each team has wired up its own credentials, its own copy of the data, and its own idea of acceptable use, so every project relitigates the same approvals and no two are governed the same way.
A platform layer resolves that by making the controls shared infrastructure. Identity, permissions, model access, policy enforcement, and logging are established once and inherited by everything built afterward, which turns approval from a bespoke negotiation into a checklist. Organizations already running individual capabilities such as AI agents or conversational AI usually adopt the platform to bring those existing efforts under one governed roof.
Governance that produces evidence, not paperwork
Boards and regulators increasingly ask specific questions: which systems make or influence decisions, what data did they consult, who authorized them, and can a particular output be reconstructed. Policy documents cannot answer that. The platform answers it from records — a catalog of every registered application with its owner and data scope, and a request-level log capturing identity, model version, retrieved sources, and policy verdict.
The same records serve operations as much as compliance. Administrators can trace a quality complaint to the exact model version that produced it, spot a team whose consumption jumped overnight, or demonstrate that a restricted collection has never been reached from an unapproved application. Regulated teams commonly pair this with compliance management so AI oversight sits in the same evidence trail as the rest of the control environment.
Built to outlast any single model generation
Model providers release, deprecate, and reprice on their own schedule, and any architecture that hard-codes one vendor inherits that volatility. Applications on the platform call a logical model name resolved centrally, so an administrator can promote a newer version, shift a workload to an open-weight model running in your own tenancy, or split traffic during evaluation without a single application team rewriting code.
That indirection is what makes long-term scale realistic: the enterprise standardizes on capabilities and controls rather than on one vendor's current best release. Explore how the platform underpins the wider Workisy AI suite and reporting through AI analytics, or arrange a platform architecture review with our team.
Results That Speak for Themselves
Measurable Impact on Your Business
Enterprise Access Control
No Provider Lock-In
Logged for Audit
FAQ
Frequently Asked Questions
Ready to See It in Action?
Book a personalized demo and discover how Workisy can transform your operations in weeks, not months.