The platform, in six parts
Each capability works standalone — turn on visibility today, layer routing and guardrails when you're ready.
Unified cost visibility
See every dollar across every provider in one dashboard. Attribute spend to teams, features, and customers with token-level accuracy — no more invoice mysteries.
AI-powered recommendations
Our engine continuously analyzes your traffic and surfaces specific, high-ROI actions: swap models, enable caching, compress prompts. Each recommendation includes projected savings.
Intelligent model routing
Automatically send each prompt to the optimal model. Maintain quality with real-time benchmarking. Cut costs by 30–50% without your users noticing a difference.
Budget guardrails
Set hard spending caps per team, app, or environment. Get early warnings before budgets blow. Auto-throttle gracefully instead of shutting down at midnight.
Caching & batching
Enable semantic caching and intelligent batching with zero code changes. Reduce redundant token spend by an average of 38% on day one.
Forecasting
Predict next month's AI bill with 97% accuracy. Get 30-day advance warnings before pricing tier jumps, runaway workloads, or anomalous spikes derail your budget.
One ledger for every model call
Most teams discover AI overspend at invoice time. SpendTensor traces every request the moment it happens — provider, model, prompt fingerprint, input and output tokens, latency, retries, and cache status. Costs are computed per call using live provider rate cards, then rolled up by team, application, environment, and customer.
- Per-request cost attribution
- Team, app, and environment tags
- Daily, weekly, and month-to-date rollups
- CSV and API export for finance
Routing that protects quality first
The routing engine benchmarks candidate models against your real traffic with held-out evaluations before a single production request moves. You set the quality floor; SpendTensor only shifts traffic when output similarity clears it — and rolls back instantly if drift is detected.
- Held-out eval benchmarking
- Configurable quality thresholds
- Gradual traffic ramping
- One-click rollback with audit trail
Budgets that stop the bleeding early
Set hard caps per team, app, or environment and get warned at 50%, 80%, and 95% of budget rather than after the fact. When a workload runs away, SpendTensor throttles gracefully or downgrades the model instead of taking your product offline at midnight.
- Hard and soft spending caps
- Email and Slack alerting
- Anomaly detection on spend spikes
- Graceful throttling and model downgrade
Coverage across every provider you use
Ingestion adapters normalize usage and pricing from each vendor so a Bedrock Claude call and a direct Anthropic call sit side by side in the same report.
Built for the whole org, not just engineering
Know exactly which service, feature, and model is burning budget — before the CFO asks. Ship faster without cost anxiety.
Chargeback and showback per team with token-level accuracy. Enforce guardrails centrally without blocking product velocity.
Forecast next month's AI bill within 3%, verify realized savings, and export clean reports on demand.
Built for regulated workloads
Metadata-only storage by default, encryption in transit and at rest, and private deploys for healthcare, finance, and government.
What teams get in the first 30 days
- A single dashboard covering OpenAI, Anthropic, Gemini, Azure OpenAI, and Bedrock
- Token-level attribution by team, app, and environment
- Prioritized savings recommendations with projected impact
- Budgets with early-warning alerts before overspend
- Accurate month-end spend forecasts
- Exportable reports for finance