The AI Cost & Governance Assessment
A fixed-scope, fixed-price engagement that shows you exactly where your Azure OpenAI spend goes, proves a quality-gated saving on one real workflow, and gives you a plan to govern every call. It is the on-ramp to running the gateway in your own tenant.
What you get
Four concrete deliverables, not a slide deck. Everything is measured or documented, and yours to keep.
LLM spend and context audit
We route a sample of your traffic through the gateway in observe-only mode and produce an itemized view of where tokens and cost go, attributed by workflow. You see exactly what your applications send to models, and which parts are bloat.
A measured compression result
We take one real workflow, build a small evaluation set, and produce a quality-gated before-and-after: input tokens removed, cost saved, and a held-out quality check that proves answers held. A real number you can take to finance.
Governance and data-flow review
We map what data reaches which model, identify exposure and policy gaps, and document the controls a context gateway would enforce: redaction, data-class routing, approvals, and an audit trail.
A deployment plan
A concrete plan to run the Quanta gateway inside your own Azure tenant, with the architecture, the identity and secrets model, and a phased rollout from observe-only to active control.
How it runs
Connect and baseline
Stand up the gateway in observe-only mode against a sample of traffic. Establish a per-workflow baseline of tokens, cost, latency, and prompt composition. No changes to your applications.
Measure and compress
Build an evaluation set for one workflow. Test compression candidates against it. Produce the measured, quality-gated cost result.
Findings and plan
Deliver the audit, the measured result, the governance review, and the deployment plan, with a working session to walk your team through it.
Engagement tiers
Fixed scope and fixed price, agreed before we start. The assessment fee is credited toward a gateway deployment if you proceed.
Focused
- Spend and context audit on one workflow
- One measured compression result
- Governance gap summary
- Outline deployment plan
Standard
Most chosen- Audit across up to three workflows
- Measured compression on the highest-spend workflow
- Full governance and data-flow review
- Detailed Azure-tenant deployment plan
Enterprise
- Portfolio-wide spend attribution
- Multiple measured results
- Security review support
- Deployment into your tenant as a follow-on
Indicative ranges for planning. Final scope and price are set in a written statement of work after a scoping call.
From assessment to a governed gateway.
Most assessments lead to a managed deployment of the Quanta gateway inside your Azure tenant, operated by Ryshe. You keep the findings either way.
Request the assessment