Platform and engineering teams use OpsCanvas to replace guesswork with verified evidence. These are the problems they faced, and the outcomes they achieved.
Whether it's backup posture, agent governance, cloud waste, or migration readiness, the underlying problem is the same: operational truth is fragmented and invisible until something goes wrong.
We had board-level commitments to a four-hour RTO. Oscar found eight production databases that had no backup plan at all. That changed the conversation immediately.
The bank had board-level commitments to a four-hour RTO and 24-hour RPO across Tier 1 systems. But its DR documentation was eighteen months old, and the live environment had drifted across services, configurations, and team ownership.
The CTO was preparing for SOC 2 AI controls, but no one could answer what each agent could access or modify. OpsCanvas mapped every production agent, credential pattern, and blast-radius boundary.
Platform leadership suspected waste, but manual reviews took weeks and produced stale spreadsheets. OpsCanvas connected cost, ownership, and runtime context so teams could act on verified waste.
Three previous migration attempts had been paused after unexpected dependencies surfaced late in the project. The engineering team was spending more time in discovery meetings than doing actual migration work. HIPAA compliance evidence requirements meant that every dependency needed documented provenance.
Every story above follows the same four-step pattern. What changes is the use case, the workstreams, and the agent skills. The governance model never changes.
The CISO received an audit notice citing concerns about AI-driven infrastructure changes that lacked documented human approval. The platform team had shipped a dozen agent workflows over the previous year, each created independently and with different credential patterns. There was no central inventory. There was no blast-radius documentation. Three agents held IAM roles with far broader permissions than their tasks required.
The audit required the insurer to demonstrate, for every agent in production: what it could access, what credentials it held, what changes it had made in the prior 90 days, and whether every material action had been approved by a human. None of that was documented in any single place. The platform team estimated six weeks of manual investigation to reconstruct the picture.
We had no idea one of our compliance-reporting agents had write access to production IAM. It had been set up that way during a rushed deployment six months ago and nobody had reviewed it since.
Head of Platform Engineering, Regional InsurerThe AI Agent Inventory and Operational Risk Assessment produced a complete agent inventory in nine days. Each agent's identity, credentials, blast radius, and recent action history was documented with evidence. Over-privileged roles were flagged with remediation recommendations. The audit trail required by the regulator was generated directly from the context graph, with provenance attached to every action record. The platform team moved from estimated six weeks of manual work to a defensible, evidence-backed posture report suitable for regulatory submission.
The CFO put a hard ceiling on cloud spend for Q3. The VP of Infrastructure needed to cut at least $800K from the annual run rate without disrupting production. The problem was that nobody could attribute cost to teams or applications with enough precision to know what was safe to cut. Every previous cost exercise had produced a spreadsheet with guesses about ownership that were outdated before they reached the finance team.
The Zombie Scan found 847 resources with no traffic or API calls in 60 or more days. These included RDS instances from a product line that had been sunset eight months earlier, EBS volumes attached to terminated EC2 instances that had never been cleaned up, and 14 NAT gateways in regions where no active workloads remained. Ownership for most of them could not be attributed from tags alone because the tagging policy had changed three times in two years and been applied inconsistently.
The Zombie Scan found $2.1M in annual waste in four days. We had spent three months trying to build the same picture from Cost Explorer and gotten nowhere near that level of detail.
VP of Infrastructure, B2B SaaS PlatformThe Cost Optimization Workflow orchestrated the decommissioning sequence with explicit human approval gates at every tier. High-confidence zombies were approved in batches. Ambiguous resources were escalated to the team leads identified through Oscar's ownership mapping. Nothing was deleted without a named approver on record. The platform team eliminated 63% of identified waste inside six weeks without a single production incident.
Cloud complexity, agent risk, and operational debt are universal. The regulatory requirements and buying conversations differ by sector.
A bank's regulator requested evidence of DR posture before a supervisory exam. The existing documentation was eighteen months old. Oscar scanned 340 production resources and generated an audit-ready DR Plan with RTO/RPO validation in eleven days.
An insurer received an audit notice requiring evidence of human oversight for every AI-driven infrastructure change. The platform team had no central inventory. OpsCanvas produced the complete inventory, blast-radius map, and 90-day action history with human-approval records in nine days.
A hospital system's EHR migration had been paused three times over two years because dependencies kept surfacing at cutover. Oscar mapped 180 services against live systems instead of documentation, producing a dependency-aware sequencing plan with HIPAA evidence provenance for every dependency.
A regional provider network needed to verify that every production system handling PHI met HIPAA backup requirements. Manual verification had historically taken eight weeks per facility and produced results that were outdated before distribution. OpsCanvas completed the full assessment across three facilities in six days.
A growth-stage SaaS company needed to reduce burn rate before closing a Series C. The VP of Infrastructure had a CFO-mandated ceiling and no way to attribute cost to products. The Zombie Scan found $2.1M in annual waste in four days and the Cost Optimization Workflow eliminated 63% of it inside six weeks.
A Series B SaaS company needed SOC 2 certification with the new AI controls addendum to close an enterprise deal. The auditor required evidence that every production agent had scoped credentials, documented blast-radius boundaries, and human-approved action records. The AI Agent Assessment delivered all three in nine days.
An 8,000-employee retailer's cloud bill had grown 40% year-over-year with no accountability for the increase. The Zombie Scan found 847 idle resources across three cloud accounts, many with no valid owner attribution due to inconsistent tagging. The Cost Optimization Workflow orchestrated cleanup with department-head approval gates, not blanket deletion.
A manufacturing company's cloud modernization program had an 18-month discovery phase driven by consulting fees and spreadsheet-based dependency mapping. OpsCanvas replaced the discovery phase by deploying Oscar against live systems, compressing the dependency map from an 18-month engagement to a 90-day project with continuous verification built in.
Every story above started with an assessment. Oscar scans your live environment, the context graph assembles the picture, and you get a verified posture report in days. Not weeks.