Context that stays in scope
Give a workflow the information it needs. Keep retrieval boundaries tied to the workspace and the task.
AI agent runtime
Give your agents a task.
Not the keys to everything.
Connect reasoning to useful actions with scoped tools, explicit handoffs, and a record of every execution.
Total requests1.28M+18.6% vs. previous period
Success rate99.98%+0.04% vs. previous period
P50 latency142ms-12 ms vs. previous period
Estimated cost$84.62-8.2% vs. previous period
Request volume
Last 24 hoursSuccessful requests1.28M total
Model routing
Atlas / fastPrimary route
68%Solace / reasonComplex tasks
24%Ember / compactFallback route
8%Active deployments 3
All healthy| Service | Region | Status | Requests | Latency |
|---|---|---|---|---|
| support-resolver | us-east-1 | Healthy | 842.1k | 142 ms |
| document-pipeline | eu-west-1 | Healthy | 318.6k | 208 ms |
| research-orchestrator | ap-south-1 | Healthy | 124.9k | 186 ms |
Support resolution flowv2.4.1 / Published
TRIGGERNew support requestwebhook / support.inboundListening
AGENTResolve with contextAtlas / fast + knowledge base98.4% resolved
GUARDRAILValidate responsepolicy / customer-safePolicy passed
Last run completed3 steps · 1.42s · $0.0021
EXECUTION TIMELINE
Context retrieval210 ms
Agent reasoning980 ms
Policy check230 ms
Trace completedsupport-resolvertr_8f2c91 · 142 ms
POST /v1/agents/runtr_8f2c91
142 ms200↳retrieve.contextsp_72a801
38 ms200↳model.generatesp_6b3f42
89 ms200↳policy.validatesp_4d8e12
15 ms200ATTRIBUTES
- environment
- production
- region
- us-east-1
- model
- atlas-fast-2
- policy
- customer-safe
EVENTS
Request accepted
Context retrieved · 4 documents
Model response received
Policy passed · response sent
Estimated spend / last 24h$84.628.2% below previous period
Cost by workload
USDsupport-resolver$48.12
document-pipeline$24.36
research-orchestrator$12.14
Budget policy active. Alert at 80% of your $3,000 monthly cap.
All systems operationalSample workspace · illustrative data
Original agent canvas with fictional tools, model names, and execution data.
01Capability, with boundaries
Useful agents need
more than a prompt.
Tools with a clear contract
Declare allowed actions, validate arguments, and separate read operations from actions that change a system.
Human review where it matters
Pause at consequential decisions. Route exceptions to the people who have the context and authority to resolve them.
02Follow the execution
From request to result.
No missing middle.
A successful response is only part of the story. Know what the agent retrieved, which route it chose, and why it called a tool.
- 01
Receive and validate the task.
Apply input constraints before the workflow consumes context or calls a model.
- 02
Reason inside a policy boundary.
Use explicit tools, bounded retries, and a budget the workflow cannot silently exceed.
- 03
Check the outcome.
Evaluate the output against the task contract, then send or escalate the result.
A CONTROLLED EXECUTION01 / 03
Receive task
Retrieve context
Check policy
Agent orchestration
Choose a model
Call a tool
Evaluate output
TRACEABLE BY DEFAULTCONTROLPLANE
03A repeatable standard
Build once. Learn on
every version.
Keep your evaluation examples alongside the changes they are meant to test.
Version the workflow
Capture prompts, context settings, tools, and routes in a single release definition.
Run your examples
Include ambiguous inputs, missing context, tool failures, and budget limits.
Inspect the differences
Compare the output and the execution path before choosing a release.
Promote deliberately
Make production an explicit decision. Keep the last known configuration available.
A few useful details
Your workflow.
Your level of control.
Can a person approve an action?
The sample product model includes explicit review checkpoints for consequential actions. This static template demonstrates that positioning; it does not run agents or approval infrastructure.
Do we have to use a particular model?
The illustrated runtime separates workflow intent from model selection. The template uses original fictional model names so a buyer can replace them with their supported providers.
What happens when a tool fails?
The sample execution model makes retries, timeouts, and escalation paths explicit. The included UI is a demonstration, not a connected runtime.
From first request to production
Make the next agent
one you can understand.
Start with a task. Keep every decision in view.