AI Agent Platform
Built for Enterprise Control
An AI agent platform is the software layer where an enterprise builds, runs, governs and monitors AI agents: the agents, the tools they use, the models they call and the audit trail they leave, all in one place. VDF AI is that platform, and it runs in our managed cloud or entirely inside your own infrastructure.
Agents, orchestration, retrieval, routing and governance in one product.
Start free in the cloud, or deploy on your own servers in two weeks.
30 minutes with a solutions architect. No slide deck.
Who evaluates an AI agent platform
- Platform and architecture teams asked to give every department AI agents without a separate stack per team
- CIOs replacing a pile of copilots and pilots with one system they can license, secure and explain to the board
- Security and compliance leaders who need agent actions attributable to a person, a policy and an approval
- Engineering leads whose framework prototype works but cannot pass a production readiness review
What VDF AI gives them
- A governed agent workspace with an MCP tool registry: VDF AI Agents
- Multi-agent orchestration on a visual canvas: VDF AI Networks
- Permission-aware retrieval over internal knowledge: enterprise RAG
- Cost, latency and energy-aware model routing: VDF AI Router
- Policy, approvals and an audit vault: AI governance platform
Where Agent Prototypes
Stop Being Enough
An agent framework leaves you to build
- Identity, SSO and role-based permissions for every tool
- OAuth connectors to the systems agents must read and write
- Logging, tracing and an audit format legal will accept
- Deployment, upgrades and secrets handling on your own
- A way to swap models when prices or policies change
- An answer when the auditor asks who approved an action
An AI agent platform ships it
- Users, roles and tool permissions inherited from your directory
- Native connectors with semantic search over each source
- Every prompt, retrieval, tool call and output written to the Vault
- Containers you run in cloud, on-premises or air-gapped
- SEEMR routing across providers on quality, cost and energy
- Approval gates and decision receipts as standard behaviour
Build. Orchestrate.
Govern.
Build agents in a governed workspace
A six-step builder turns a role, a knowledge source and a set of tools into a working agent. Tools come from an MCP registry your admins curate, so an agent can only reach what it has been granted.
Orchestrate agents as networks
Networks connect specialist agents into a directed graph with shared state, retries and per-node cost and energy telemetry. A researcher, a drafter and a compliance reviewer collaborate on one task and leave one trace.
Govern every run
Policies decide which models, tools and data each role may use. Risky actions wait for a human. The Vault keeps a durable record of each decision so an audit is a query, not an investigation.
How the options compare
| Dimension | Agent framework | Vendor copilot suite | VDF AI platform |
|---|---|---|---|
| Where it runs | Wherever you build the hosting | The vendor's cloud tenant | Managed cloud, private cloud, on-premises, air-gapped |
| Model choice | Any, wired by hand | The vendor's models | Any provider or open-weight model, routed automatically |
| Multi-agent orchestration | Code you maintain | Limited to the suite's flows | Visual networks with shared state and telemetry |
| Governance and audit | Build it yourself | Vendor's logs, vendor's format | RBAC, approval gates and an immutable Vault |
| Enterprise connectors | Community plugins | Deep inside one ecosystem | Native OAuth connectors across ecosystems |
| Pricing model | Engineering time | Per user plus per message | Per user in cloud, capacity pool on-premises |
Eight things to check before you choose an AI agent platform
This is the short version of the questions procurement teams in regulated industries put to vendors. The full 66-question set is in the enterprise AI agent RFP checklist.
- Deployment you controlManaged cloud for speed, and the identical platform on-premises, in a sovereign region or fully air-gapped when the data demands it.
- Model freedomOpen-weight and commercial models side by side, with routing that picks the cheapest model that meets the quality bar for each request.
- Multi-agent orchestrationAgents that hand work to each other on a visual canvas with retries, state and per-node telemetry, not a single chatbot with plugins.
- Enterprise connectors with identityMicrosoft 365, Google Workspace, Atlassian, GitHub, Slack and Notion connected through OAuth so agents only see what the user may see.
- Governance in the runtimeRole-based access to tools and knowledge, approval gates for risky actions, and an immutable record of every prompt, retrieval and output.
- Evidence for regulatorsEU AI Act, DORA and sector audits ask who triggered an agent, what it touched and who approved it. The platform must answer from logs, not from memory.
- Pricing you can forecastPer-user cloud plans or an annual on-premises capacity pool, never a per-run meter that punishes you for automating more.
- A path from pilot to productionReady-made agents, a tool catalogue and playbooks so the first governed workflow ships in days rather than after a platform build.
Choose the deployment mode that matches your data
The platform is the same in every mode. What changes is where the models run, where the vector index lives and who holds the keys.
- On-Premises AI PlatformDeployed in your datacentre by VDF AI engineers, production in two weeks.
- Private AI Agent PlatformArchitecture, controls and trade-offs for this deployment mode.
- Self-Hosted AI Agent PlatformArchitecture, controls and trade-offs for this deployment mode.
- Sovereign AI Agent PlatformArchitecture, controls and trade-offs for this deployment mode.
- Air-Gapped AI Agent PlatformArchitecture, controls and trade-offs for this deployment mode.
- What is an on-premise AI agent platform?The definitional guide behind this page.
- Compare 28 platformsLyzr, Copilot Studio, Agentforce, LangGraph, CrewAI, watsonx and more.
- Browse the agent catalogueReady-made agents for banking, HR, sales, compliance and engineering.
Questions buyers ask about AI agent platforms
What is an AI agent platform?
An AI agent platform is the software layer where an organisation builds, runs, governs and monitors AI agents in one place: the agents themselves, the tools they call, the models behind them, the knowledge they retrieve and the audit trail they leave. It differs from an agent framework, which is a code library, and from a copilot, which is a single vendor's assistant bound to that vendor's cloud.
How is an AI agent platform different from an agent framework like LangChain or CrewAI?
A framework gives developers building blocks for one agent or one workflow; the team still has to add identity, permissions, connectors, observability, deployment and audit before it is safe in production. An AI agent platform ships those layers as the product. VDF AI can also register agents built with frameworks so they inherit the same governance, which is how many teams migrate.
Can an AI agent platform run entirely on-premises?
Yes. VDF AI runs as containers inside your own datacentre, private cloud or air-gapped network, with models served on your GPUs and retrieval over your own document stores. The same agent and network definitions also run in VDF AI's managed cloud, so teams can start free in the cloud and move on-premises without rebuilding.
Is VDF AI an enterprise agent platform or AI agent software for individual users?
VDF AI is an enterprise agent platform. It is licensed for whole organisations, integrates with single sign-on and role-based access, and is designed for teams in regulated industries that need every agent action to be attributable and reviewable. A free cloud starter plan exists so individual engineers can evaluate it before an enterprise rollout.
How does VDF AI compare with Lyzr, Microsoft Copilot Studio or Salesforce Agentforce?
Copilot Studio and Agentforce are strongest inside their own ecosystems and bill per message or per conversation. Lyzr focuses on fast agent productionisation with per-run pricing. VDF AI is built for governed multi-agent orchestration across many enterprise systems, vendor-supported on-premises deployment, EU AI Act evidence and capacity-based licensing. Side-by-side breakdowns are on the compare pages.
See enterprise AI agents in production
Watch how VDF AI runs governed, multi-agent workflows on your own infrastructure — then compare it against the platforms you are evaluating.