Visibility & attribution
Make every euro traceable to something a person is accountable for.
- Billing export and data model
- Tagging strategy
- Showback and chargeback
- Power BI reporting
- Anomaly alerting
FinOps
Control the economics of cloud and AI.
TekLid turns Azure and AI spend into something finance and engineering read the same way — attributed, forecast and optimized, without turning every deployment into a budget negotiation.
- Spend attributed to teams and products
- Optimization ranked by saving and effort
- AI usage costed per use case
What we put in place
Cost as an architectural property, not a monthly surprise.
Reporting, optimization and governance that hold once the engagement ends.
Optimization
Reduce the bill without reducing what the platform can do.
- Rightsizing
- Reservations and savings plans
- Storage lifecycle policies
- Idle resource removal
- Architecture efficiency
AI FinOps
The cost discipline most AI programmes discover far too late.
- Model and token cost analysis
- Per-use-case unit economics
- Prompt and context efficiency
- Model routing and tiering
- Capacity planning
Governance
Guardrails that keep spend from drifting back after the cleanup.
- Budgets and policy guardrails
- Forecasting
- Cost review cadence
- Engineering accountability
- Cost-aware architecture standards
Outcomes
What good cost governance looks like.
Spend that has an owner
Every euro maps to a team, product or environment instead of an untagged resource group.
Savings that survive
Optimizations are encoded as policy and architecture standards, so costs do not quietly drift back.
Forecasts finance can use
Committed, variable and AI spend are modelled separately, with the assumptions written down.
AI you can budget
Each assistant carries a measured cost per conversation, per user and per month.
Deliverables
What you receive.
A reporting model, a ranked backlog and an operating cadence — all of it yours to run.
- Cost data model and reporting
- Tagging and attribution standard
- Ranked optimization backlog
- Reservation and commitment plan
- AI unit economics model
- Monthly FinOps operating cadence
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