Receive the request
Take one agreed input from a test ticket or support queue. Record the request ID and separate each user's permitted data.
AI delivery · one workflow first
One useful AI workflow.
One useful AI workflow.
A result your team can verify.
Turn an IT support request into a cited recommendation and a reviewable next step. Start with one workflow, approved knowledge and a named human owner — before connecting an agent to production actions.
A scoped engineering engagement, not a subscription to a ready-made autonomous agent. Price, access and delivery dates are agreed before work starts.
AI agent developmentSERVICE ARCHITECTURE
Illustration of the service approach.
One workflowOne team, one owner and an agreed boundary.
Read-only firstNo production actions during initial evaluation.
Evidence at handoverTest cases, failures, cost and operating limits.
A separate go/no-goA pilot does not automatically become production.
Start with support request → grounded recommendation.
An example scope to agree before delivery — not a claimed customer deployment. The same pattern can support incident triage when the inputs and permissions fit.
Retrieve approved context
Search an agreed knowledge source using scoped access. Attach citations; flag missing or conflicting evidence instead of inventing an answer.
Prepare and review
Draft a summary, proposed response and next action. A named reviewer approves, rejects or sends it back. No arbitrary shell commands or model-selected destinations.
Record the outcome
Save the decision and, only after approval, create or update one permitted test task. Repeated delivery must not create duplicate tasks.
A pilot with a finish line.
Included in the agreed scope
One workflow and team; one approved knowledge collection; one input integration; one output or task integration in an isolated environment. Additional systems are separately scoped.
What you receive
Architecture and permission map, working pilot, evaluation dataset and results, failure log, cost assumptions, handover runbook and a go/no-go report.
What your team provides
A process owner, representative examples cleared for testing, permission to use each source, a test environment and a reviewer able to judge the output. Do not send credentials in the enquiry form.
We agree acceptance criteria before connecting tools.
Thresholds follow your baseline and risk tolerance. We do not promise an unmeasured time saving or a universal accuracy percentage.
Useful output
Reviewers assess source-backed answers and the proposed next step against a held-out set. Missing evidence must result in a clear handoff.
Enforced boundaries
Test denied access, another user's records and malicious instructions inside retrieved material. A prompt alone is not an authorization control.
Safe failure
Repeat the same event, reject approval, time out an integration and lose a dependency. Check that failures remain visible and no unapproved or duplicate action occurs.
Operable handover
Measure observed latency and cost on the agreed test set. Assign an owner, define retention and document stopping, recovery and rollback.
The workflow comes first. Placement follows.
We keep the existing Google Cloud, private and hybrid delivery options. Region, service availability, data flow and operating responsibility are confirmed during scoping.
Google Cloud
For teams with an approved Google Cloud boundary. Choose managed retrieval, model and runtime services to fit the workflow — not because every component needs to be new.
Private / on-premises
For approved local inference or data requirements. Capacity, model quality, hardware, patching and connectivity remain explicit responsibilities.
Hybrid
Keep source systems private and expose only the agreed retrieval or tool interfaces. Review exactly what crosses the boundary, with which identity and under which policy.
Existing service, clearer starting point
Start with a bounded pilot. Decide on production afterwards.
Our existing Vertex AI Agent Pilot accelerator is the Google Cloud starting point. Private or hybrid requirements receive their own scoped proposal; the accelerator's price is not a blanket price for every architecture.
Production rollout, ongoing support, extra connectors and autonomous remediation are not implied by a pilot. They need separate acceptance, an operating owner and an agreed change scope.
What can you inspect today?
AgentOps Control Plane is an early-stage, simulated interface prototype. It illustrates trace and policy concepts; it is not evidence of a hosted production service or a customer deployment.
No private CRM records, call transcripts or customer environments are used as public proof. For your pilot, the meaningful evidence will be the agreed end-to-end test pack and results.
Technical basis, not a delivery reference
These Google Cloud sources describe platform mechanisms. They do not certify this service or prove a customer result. Exact product selection and availability are checked for your project.
Bring one workflow, not a platform shopping list.
Tell us what arrives, what a good result looks like, which systems are involved and who owns the decision today. We will scope the smallest useful pilot and its acceptance criteria.
From review to practice
Practical kits for your next engineering task.
English-language guides, templates and exercises for working through a specific problem.
MCP Security & Agent Ops
Document tool permissions, review risks and assign incident responsibilities with editable templates.
n8n Recovery Drill Kit
Inspect workflow exports locally and use the workbook to plan an isolated recovery drill.
AI Coding Guardrails
Practise repository rules, independent checks and plan-only Terraform in eight modules and four guided labs.