Our Services
Consulting and advisory across agentic platform engineering and the operational intelligence it runs on - from observability and inventory through to FinOps, governance, and unified XOps practices.
Unified Operational View
Cloud Operations and Observability
One operational view across every cloud, platform, and SaaS service you run.
Most enterprises run telemetry in silos - one tool for AWS, another for GCP, separate dashboards for Databricks, Snowflake, Kubernetes, and the SaaS estate. Incidents span those silos. Root cause doesn't respect provider boundaries. Operating at enterprise scale means stitching signals together manually, and by the time the picture is complete the incident is either resolved or escalated.
StackQL Studios designs and delivers unified operations and observability programmes across heterogeneous estates. We consolidate telemetry, build the operational practices and runbooks that sit on top of it, and integrate Claude-powered agents into triage and summarisation workflows where they can accelerate first-line response. The result is a single operational view that reflects what's actually running and what's actually happening to it.
Key Benefits
- Unified telemetry across cloud, SaaS, data platforms, and Kubernetes - one pane, not six
- Operational runbooks and on-call practices calibrated to your actual estate and incident patterns
- Agent-assisted triage and summarisation using Claude, grounded in live operational state
- Integration with existing observability stacks (Datadog, Grafana, New Relic, Splunk) rather than forced replacement
- SLO instrumentation and error-budget practices that survive contact with reality
What We Deliver
- Observability architecture review and consolidation roadmap
- Cross-cloud dashboards and SLO instrumentation
- Incident response runbooks and on-call practice uplift
- Claude-powered triage agents for first-line incident response
- Ongoing advisory as your estate and tooling evolve
Query-Native Inventory
Inventory and Asset Intelligence
Know exactly what you have - across every cloud, every region, every account, every SaaS.
Most enterprises underestimate the size and complexity of their cloud and SaaS estate. Shadow infrastructure, orphaned resources, multi-account sprawl, and untracked SaaS make it nearly impossible to maintain an accurate inventory through dashboards and export files alone. The gap between what's documented and what's actually running only widens over time.
StackQL Studios builds living, queryable inventories of every resource across your AWS, Google Cloud, Azure, Kubernetes, and SaaS environments. Rather than polling dashboards or stitching together CSV exports, we query provider APIs directly - giving you accurate, structured data you can join, report on, and feed into downstream governance, FinOps, and agentic workflows. The inventory isn't a one-off deliverable; it's a capability your other programmes build on with confidence.
Key Benefits
- Comprehensive asset inventory across all accounts, regions, providers, and SaaS services in a single queryable view
- Automated drift detection - know when resources appear or disappear outside approved change processes
- Tagging compliance reporting that identifies untagged or incorrectly tagged infrastructure
- Exportable, API-accessible inventory data compatible with your CMDB, ServiceNow, or internal data platforms
- A foundation that downstream services (FinOps, governance, agentic workflows) can build on directly
Questions We Help You Answer
- What resources exist across every account, region, and provider right now?
- Which assets appeared or disappeared outside approved change windows?
- Where is infrastructure running that nobody claims to own?
- Which resources are missing required tags or ownership metadata?
- How does our SaaS estate (GitHub, Okta, Databricks, Snowflake) sit alongside our cloud estate?
Unit Economics & Accountability
FinOps
Turn cloud spend into a concrete accountability model, not just a report.
Cloud cost overruns rarely stem from a single cause. They accumulate through idle resources, over-provisioned instances, unattached storage, inefficient data transfer, missed commitment opportunities, and SaaS spend that nobody owns. Identifying these patterns at scale requires querying spend and usage data alongside the actual resource configuration and the teams responsible for it.
StackQL Studios builds FinOps programmes that correlate billing data with live infrastructure state and organisational ownership. We establish unit economics (cost per customer, per workload, per product line), build the accountability model that ties spend to teams, and deliver the tooling - dashboards, anomaly detection, rightsizing recommendations - to keep it working without manual effort. Where appropriate, Claude-powered agents handle first-line investigation of anomalies and produce the summaries your FinOps function would otherwise write by hand.
Key Benefits
- Unit economics calculated across cloud, data platform, and SaaS spend, tied to workloads and business owners
- Resource rightsizing analysis correlating actual utilisation metrics with current instance types and sizes
- Idle and orphaned resource identification - unattached volumes, stopped instances, unused load balancers
- Reserved instance, Savings Plan, and CUD coverage analysis with purchase recommendations
- Ongoing anomaly detection with agent-assisted investigation of unusual spend patterns
Typical Outcomes
- 20-40% reduction in annual cloud spend across engagements
- Clear cost accountability by team, workload, and product line
- Commitment coverage optimised across RIs, Savings Plans, and CUDs
- Anomaly detection that surfaces overruns within hours, not billing cycles
- FinOps practice embedded in engineering workflows, not bolted on after the fact
Continuous Policy Evidence
Access Governance and Posture
Continuous, queryable evidence of who can do what across your estate, and whether it matches policy.
Governance splits into two questions most organisations answer with different tools, different teams, and different cadences: who can access what (IGA, entitlements) and is what they can access configured correctly (CSPM, posture). Both decay continuously. Service accounts accumulate permissions. Storage buckets drift public. Admin accounts go dormant but retain access. MFA lapses. Quarterly reviews and annual audits catch some of it, too late.
StackQL Studios builds continuous, query-driven governance programmes that treat access and posture as one problem with one source of truth. We query IAM layers across every cloud and SaaS provider, run posture checks against CIS, NIST, SOC 2, and custom policy frameworks, and integrate with your identity provider for end-to-end visibility. Findings are traceable to the exact API call that produced them - unambiguous evidence for remediation, audit, and board-level reporting. Agentic workflows handle the triage and evidence-gathering that used to consume security team hours.
Key Benefits
- Continuous monitoring of IAM roles, policies, and permission boundaries across all cloud and SaaS providers
- Automated posture checks against CIS Benchmarks, NIST 800-53, SOC 2, PCI-DSS, and ISO 27001
- Detection of privilege creep, dormant admin accounts, and over-permissive service principals
- Evidence packs ready for internal audits and third-party assessors, traceable to live API state
- Integration with Okta, Azure Entra ID, AWS IAM Identity Center, and Google Workspace
- Agent-assisted investigation and remediation guidance for high-severity findings
Questions We Help You Answer
- Who can access what across every cloud and SaaS platform we use?
- Which identities hold privileges they no longer need or never should have had?
- Where do privilege escalation paths exist across our cloud accounts?
- Which resources are out of compliance with CIS, NIST, or our internal policies?
- Can we produce audit evidence on demand, not after weeks of preparation?
Claude-Grounded Agents
Agentic Platform Engineering
Build agentic platforms that work in production, not just in demos.
Agents are only useful when they can see, reason about, and act on real infrastructure - with the context, tools, and guardrails to do so safely. Most enterprise AI projects stall at exactly this step. The demo works in a notebook; production requires platform engineering that generalist AI consultancies and internal teams retrofitting Claude onto slide decks rarely deliver.
StackQL Studios is Claude-first by conviction. We design and deliver the platform substrate that makes agentic workflows viable in enterprise environments: MCP server design, agent SDK applications, Claude Code rollouts, context engineering for long-running workflows, evaluation frameworks, and the guardrails and observability to run agents against real systems with real consequences. Our work is grounded in the operational intelligence we build elsewhere in the practice - inventory, observability, governance - because agents are only as good as the context they're given.
Key Benefits
- MCP server design and implementation exposing your internal tools and data sources to Claude safely
- Claude Code rollouts across engineering teams, with the enablement and guardrails to scale them
- Agent SDK applications for ops, support, finance, and platform engineering workflows
- Context engineering, evaluation, and observability for production agentic systems
- Human-in-the-loop gating and policy controls calibrated to your risk posture
- Governance patterns for agent identity, audit trails, and accountability
What We Build
- Custom MCP servers connecting Claude to your enterprise systems
- Agentic workflows for incident response, cost anomaly investigation, and access certification
- Claude Code practice uplift across engineering organisations
- Evaluation harnesses and regression suites for production agents
- AgentOps: the operational practices and tooling to run agents like any other production system
One Operating Model
Multi-Cloud XOps
One operating model across every cloud, every platform, every discipline.
Most enterprises end up with parallel operating models: one set of DevOps practices for AWS, another for GCP, a third for Azure, separate DataOps for Databricks and Snowflake, a disconnected MLOps practice, and SecOps layered on top trying to keep up. The cost is real - duplicated tooling, inconsistent controls, fragmented skills, and engineering time lost translating between environments.
StackQL Studios designs and delivers unified XOps practices across heterogeneous estates. We establish common pipelines, shared tooling, and consistent operating models across DevOps, DataOps, MLOps, SecOps, and emerging AgentOps - so teams deliver the same way regardless of provider. Where it makes sense, we migrate production Terraform to stackql-deploy for a query-native deployment approach with built-in drift verification, and fold agentic workflows into the pipeline to accelerate routine work.
Key Benefits
- Unified CI/CD and deployment patterns across AWS, GCP, Azure, and on-prem
- Shared DataOps and MLOps practices spanning Databricks, Snowflake, and cloud-native data services
- SecOps and AgentOps integrated into the same pipeline, not bolted on
- Optional migration from Terraform to stackql-deploy for query-native IaC with built-in drift verification
- Platform engineering capability uplift, runbooks, and training for your teams
What the Engagement Looks Like
- Current-state assessment across delivery, data, and security pipelines
- Target operating model design spanning DevOps, DataOps, MLOps, SecOps, and AgentOps
- Phased consolidation with equivalence testing at every step
- Optional IaC modernisation (Terraform to stackql-deploy) where it makes sense
- Enablement and training for platform engineering teams
Not sure where to start?
Get in touch and tell us what you're working on. We can help you figure out the next steps.
Get in Touch