Scoped discovery
Read-only access through approved connectors, using the permissions your engineers already hold. No credentials stored centrally.
AI Optimization
What your AI is doing, what it costs, and what it risks. Automatically.
OpsCanvas surfaces AI operational intelligence from your live cloud environment in days, with no tagging or instrumentation required. Start with an assessment in the area that hurts most. Findings feed directly into Oscar for governed, co-pilot remediation.
Daysfrom assessment to deliverable
4AI assessments on one Context Graph
0tags or agents required to start
100%of remediation actions human-approved
Why This Exists
AI adoption outran AI accountability.
Every enterprise now runs LLM workloads, agents, and GPU fleets. Very few can say what they cost, who owns them, or what they can touch. OpsCanvas answers those questions from live infrastructure, because the Cloud Intelligence Graph already knows what is running, and turns every finding into governed work rather than another report on a shelf.
AI Assessments
Start where it hurts most.
Two cost assessments, two risk assessments. All four run on the same Context Graph, so each additional assessment stacks on the graph you already built.
AI Cost Intelligence
AI Token Optimization
Map every AI API dollar to the team, workload, and environment that generated it. Surface unattributed spend and forecast runaway growth before the CFO asks.
Delivers
- Attribution map across Bedrock, Azure OpenAI, Vertex AI, and direct APIs
- Spend trend analysis and forward forecast
- Token budget recommendations by team and application
AI Cost Intelligence
GPU Optimization
Identify idle, underutilized, and over-provisioned GPU capacity across training and inference, with full IaC lineage so reclaim decisions are defensible.
Delivers
- Full GPU fleet inventory: utilization, owner, project, environment
- Cost attribution with 90-day trend and idle classification
- Right-sizing roadmap with estimated annual savings
AI Risk & Governance
Agent Risk
Discover every AI agent in your environment, including the ones nobody knew existed. Map blast radius, classify autonomy, and surface the agents most likely to cause an incident.
Delivers
- Complete agent inventory with blast radius analysis
- Autonomy classification: fully autonomous, supervised, HITL
- Token governance gaps and security oversight scoring
AI Risk & Governance
AI Data Governance
Enumerate which databases, buckets, and data stores each AI agent can reach, classify exposure, and surface regulatory risk before a breach forces the question.
Delivers
- Data Exposure Matrix: agent by data store by classification
- PII and sensitive data in AI context window risk scoring
- Compliance gap mapping: GDPR, HIPAA, EU AI Act
AI Operations: Oscar runs the daily loop.
Oscar works as a co-pilot inside your cloud perimeter: scanning continuously, answering operational questions grounded in the live Context Graph, and proposing remediation actions that an engineer approves before anything executes. Assessment findings feed directly into Oscar's task queue, turning report items into governed, audit-trailed work.
Continuous scanningGrounded operational answersApproval-gated remediationFull audit trail
The Engagement Arc
From assessment to continuously governed AI.
Offerings can be run individually or bundled across categories. Every engagement follows the same arc, and every stage is evidence-backed.
01
Assessment
Oscar scans the environment and builds a live Context Graph. Evidence-backed deliverable in days. Can be purchased standalone.
02
Report & Roadmap
Findings delivered as a structured report with a prioritized remediation roadmap. Each item is an Oscar-ready task with blast radius and owner context attached.
03
Oscar Remediation
Oscar works through the roadmap in co-pilot mode alongside an engineer. Oscar proposes. The engineer approves. Every change is logged with a full audit trail.
04
Ongoing Monitoring
Quarterly, monthly, or continuous reassessment. Catch drift, new agents, and spend growth before they become incidents.
Security Model
Built to be trusted inside your perimeter.
Assessments run as two scoped, deterministic, approval-gated phases: inventory discovery through approved connectors, then deterministic policy checks against that inventory. Oscar never performs open-ended network scanning, and no action executes without explicit human sign-off.
Deterministic checks
Policy checks run deterministically against the discovered inventory. Same inputs, same findings, every time.
Human-approved action
Nothing executes without explicit sign-off. Oscar proposes, an engineer approves, and every change carries an audit trail.
Get Started
Bring accountability to your AI footprint.
Start with the assessment that answers the question your leadership is asking right now. The Context Graph you build powers every engagement after it.