Make complex work move forward.
Put agents to work across the systems and decisions that matter — with your people in control and your data where it belongs.
Explore solutionsEvery enterprise has a decision like this.
Documents in, evidence gathered, a cited recommendation, a person accountable for the call. Agents take the middle of the workflow; your people keep the decision — whatever the industry.
Prior authorization, with the evidence in view.
A request arrives with clinical records, policy criteria and missing context a reviewer must reconcile.
- 01 · Intake
Normalize the request and attach the clinical record.
- 02 · Evidence
Pull the clinical context the criteria turn on.
- 03 · Rationale
Draft a cited rationale against policy.
- 04 · Decision
A clinician reviews and approves.
Workflows shown are illustrative patterns, not reported customer deployments or outcomes.
From the first question to a running agent.
Explore the platformGive teams a co-worker, not another tool.
Ask, build and run agents through chat, CLI or API. Task-specific evaluations guide improvements in quality and cost.
02 / AI GatewayKeep control as AI spreads.
Route models and agents behind a shared identity, policy and audit layer, across teams and providers.
03 / Inference PlatformRun open models on your hardware.
Dedicated endpoints and hardware-aware optimization support the agent workloads you bring to production.
Start with the work. Build for your environment.
Define the workflow
Identify the decision, the source systems, the people who review it and the criteria for success.
Build and evaluate
Connect data and tools, test agents against task-specific evaluations and keep humans at approval points.
Deploy and operate
Run in a cloud, your VPC or on-prem, then monitor quality, policy and cost as work changes.
Your operating boundaries are part of the design.
Identity, permissions, human review and audit belong in the workflow. Explore the security approach and options for keeping data and models within your perimeter.
Inspect the method, not just the headline.
Assess inference with the measures that matter to your workloads: first-token time, throughput, end-to-end latency and cost per completed task. Request a measured evaluation for your own environment.
What work should move next?
Tell us about your workflow, systems and constraints. We’ll find the right starting point together.