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Synthesis SpendOps Public Beta

Synthesis SpendOps

Turn tokens into tELEmetry.

Synthesis SpendOps turns AI spend into delivery telemetry — attributed to features and PRs with confidence, not fake precision. From spec-first requirements to budget gates in CI.

Audit-ready allocation
Forecast vs actual
Enterprise-ready

AI verschiebt den Engpass.

Weniger Tipparbeit. Mehr Iteration. Die Kosten entstehen in Tokens, Modellwahl, Kontextwechseln und Rework – nicht nur in Stunden.

Viele sehen das nur als Monatsrechnung. SpendOps macht es zu einem steuerbaren Delivery-Signal – pro Feature, pro PR, pro Team.

Gerade in regulierten Umgebungen zählt auditierbare Transparenz: wo Spend entsteht und warum.
Status quo

Budget als Blackbox

Keine Feature-Zuordnung

Synthesis SpendOps
Feature A$42.50 (High Conf)
Rework$12.20
Forecast in Range

Four pillars for control.

A delivery layer for AI spend: from specs and forecasting to telemetry, confidence allocation, and governance.

Spec-first requirements
Contract-grade, reviewable, audit-ready

Specs become a contract: standardized, diffable, reviewable, and audit-ready.

  • Standard story template
  • Versioned like code
  • Less rework & loops
Forecasting

Forecast time and AI budget before the first commit — with uncertainty bands.

Uncertainty band +/- 20%
Risk premium Integration
Telemetry & allocation

Don’t guess spend — measure it. Attribute usage to PRs/features with confidence.

{ confidence: 0.92, pr_id: 124 }
SpendOps governance
Policies, budgets, gates

Optional, but enforceable: PR checks, budget caps, and policy guardrails. Stop-the-line for outliers.

Budget caps
Hard/soft limits & alerts
Policy engine
Allowed models & limits
CI/PR gates
Block on violation
How it works

3 steps. Operationally controllable.

Progressive disclosure: essentials on the landing — depth in the docs.

Plan & forecast
Spec-first requirements + forecast (time & AI budget) before the first commit.
Measure & allocate
GitHub events + usage reconciliation → allocation with confidence (default PR-level).
Learn & govern
Forecast vs. actual + cause clusters. Optional: budget gates & policies in CI.
Use Cases

Clear outcomes for every role.

Role-based views reduce friction across Engineering, Product, and FinOps: one ledger, one language.

Engineering
Cost per feature, burn rate, rework signals — with confidence, not fake precision.
Product & Business
Forecasts with uncertainty bands. ROI on the feature level.
FinOps
Guardrails in the flow: caps, alerts, policies — audit-ready and enforceable.
Security & Compliance

Trust by design — enterprise-first.

Capabilities, not overclaims: clear controls, audit-ready accountability, and deployment options.

Least Privilege
Minimal scopes, clear roles, no secrets in clients.
Auditability
Audit trail for policies, forecasts, overrides, and allocation inputs.
Data Residency
Cloud or private deployment — depending on your compliance profile.

Make AI spend controllable
without a black box.

If you ship with AI and you care about auditability, we’ll show you how to turn token cost into accountable delivery telemetry.