Who We Help · CFO-Facing IT / Platform Owner
Agentic AI for CFO-Facing IT & Platform Owners — Cost Per Successful Workflow, Not Cost Per Token
You're the person who has to explain the AI bill. We route every AI call through a proxy that logs workflow, model, tokens, latency, and outcome; enforce a quality floor per workflow; attach budget caps to workflows instead of seats; and tie every dollar to a named business KPI — so 'what did we get for it?' becomes a dashboard, not a spreadsheet.
Where the friction lives
- ›Nontechnical staff already past the pilot phase with unpredictable subscription spend
- ›No way to route lower-priority work to cheaper models
- ›AI cost measured by seat or MAU — neither reflects value
- ›Fragmented logs across Copilot, Anthropic, OpenAI, and internal gateways
- ›'What did we get for the AI bill?' has no defensible answer
High-ROI use cases
Cross-provider log normalization
One event stream across Copilot, Anthropic, OpenAI, Bedrock, and self-hosted with user, team, workflow, and outcome.
One dashboard, all providers
Quality floors + shadow routing
Per-workflow quality floors defined with the process owner and validated in observe-only mode before active routing.
Baseline floor validated
Budget by workflow
Caps attach to workflows, not seats; overrides logged with justification.
±10% budget variance
Outcome attribution
Every routed call tied to a downstream business signal — resolution, cycle time, cost avoidance.
>80% AI spend tied to a KPI
How we help
Shadow first, active second
We route in observe-only mode long enough to validate quality floors before real traffic switches.
Budget by workflow
Copilot seats is a procurement view; cost per resolved ticket is a management view. We deliver both.
Vendor-neutral
Anthropic, OpenAI, Azure OpenAI, Bedrock, and self-hosted are equal routing targets — no channel-partner bias.
CFO-ready reporting
Board-shaped dashboards that answer 'what did we get for it?' without translation.
In your stack
The proxy layers on top of your existing gateway — LiteLLM, Kong, Istio, or custom — no rip-and-replace.
Engagement model & pricing
6–10 week fixed-fee build, longer if call paths aren't already centralized. Weeks 1–3: log normalization + workflow mapping. Weeks 4–6: shadow routing + quality floors. Weeks 7–8: active routing + budget caps. Weeks 9–10: outcome attribution + handoff. Optional monthly optimization retainer.
What you get
- Cost per successful workflow — not cost per token
- Vendor-neutral routing across cloud and self-hosted
- Budget caps by workflow with alerts and overrides
- Board-shaped dashboards for the AI bill
- Typical 30–60% cost-per-workflow reduction inside one quarter
Frequently asked questions
Isn't this just LiteLLM or an API gateway?+
Those are components. This engagement wires them into workflow-level quality floors, budget policies, and outcome attribution.
Will routing degrade quality?+
Only within the quality floor you set per workflow. Shadow routing validates the floor before real traffic switches.
How is this different from cloud FinOps?+
Cloud FinOps covers infrastructure. AI FinOps adds model choice, quality floors, and workflow-level outcome attribution.
Can we route across cloud + self-hosted?+
Yes. Self-hosted (vLLM, Ollama, Bedrock custom) is a first-class routing target.
How fast do savings appear?+
Typical clients see 30–60% cost-per-workflow reduction within one quarter of active routing, without measurable quality loss.