Your applications hold the process. Your agents need the authority.
Deploy agentic AI at scale, on enterprise-grade infrastructure, with the delegation boundary decided by the business rather than by a vendor.
Applicationsintegrated
- and many more
Modelsconnected
- and many more
Infrastructuressupported
- On Premise
- and many more
Why agentic, and why now.
A chatbot answers. An agent acts. The moment software can act inside your core systems, the hard question stops being technical and becomes a governance question. What is it allowed to do. Who owns the outcome. When does a human decide. And how do you prove any of it afterwards.
Plenty of enterprises now have a shelf of promising demos and very little in production. The gap is rarely model quality. It is the absence of a governed place to put an agent to work.
Pilots are easy, because nothing is at stake. Scale is hard, because everything is.
Enterprise AI Solutions Architecture
Agent Core
Built once, shared.
The enterprise-grade agentic infrastructure. It is what the system is able to do. Harness and agent runtime: the agentic loop, context assembly, sandboxing, durability, orchestration. Knowledge plane: data and lineage, semantics and ontology, agent memory. Integration and action gateway: registry, tool broker, MCP, A2A, APIs, RPA. Inference and model routing: model portfolio, gateway, caching, batching, fallback.
Agent Hub
Built per use case.
The agent design and run environment. It is what the business has authorized the system to do. Policy and the delegation boundary: what stays deterministic code, what is delegated to model judgment. Agents: roles, skills, tool grants, sub-agent topology, handoffs. Human authority and interaction: delegated decision rights, approval gates, escalation paths, audit trail.
We build your Agent Core once. Your Agent Hub is where the business decides what to trust it with.
Enterprise AI Foundation
Assurance and GRC
Controls that a risk committee will accept, evidenced rather than asserted.
Identity and authorization
Agents get identities and scoped permissions, like any other actor in your estate.
Evaluation and observability
You can see what the agent did, why, and whether it is getting better or worse.
FinOps and unit economics
Cost per outcome, not cost per token. The number a CFO can hold you to.
Forward Deployed Engineers
FDEs sit with your business people and your engineers, inside your processes and your codebase. They ship Agent Core into your estate and Agent Hub into your workflows, alongside AI Engineers tuning the models, context and evaluations behind them.
- Define the outcome as a measurable unit of value, not a use case title
- Stand up enough Agent Core to carry the first live workflow
- Put one agent into production behind a human approval gate
- Build the evaluation harness before widening the boundary
- Scale to the next use cases on infrastructure that already exists
Everything connects through one governed surface.
Core systems
SAP, Oracle, IFS, Workday, Salesforce, Databricks, Snowflake.
Ecosystem
Customers, suppliers, logistics partners, bank integrations, regulator integrations, third parties.
Operations
Plants, warehouses, stores and branches, logistics, and the processes that run across them.
The integration and action gateway is the governed tool surface and the real security perimeter. It is the reason you can extend agents into your ERP without extending your risk.