Ship AI features without losing control of spend, data, or margins. One SDK gives your team cost governance, predictive intelligence, and compliance guardrails — from first prototype to production scale.
One SDK wraps them all. Track costs, enforce budgets, and detect anomalies across every provider.
From visibility to monetization — every tool you need to manage AI spend at scale.
See exactly where every dollar goes the moment it's spent. Break down costs by feature, model, customer, and environment — with dashboards that update in real time, not end-of-month.
Set hard spending limits at the org, feature, or environment level. When the budget is hit, calls are blocked automatically — no exceptions, no surprises.
ML-powered anomaly detection catches spend spikes that rule-based systems miss. Our models learn your org's normal patterns, and the circuit breaker kicks in before cost spirals.
Turn AI costs into a revenue line item. Set pricing rules per customer, generate invoices automatically, and export to your billing stack.
Know exactly what every agent session is spending in real time. Set budget ceilings in the dashboard that automatically halt sessions before they overspend — admins configure limits, engineers never touch dollar amounts.
Go from reactive to predictive. ML models trained on your data forecast spend, predict budget breaches before they happen, and surface margin-negative customers before you lose money on them.
Detect PII, PHI, API keys, and financial data in prompts before they reach third-party LLM APIs. Growth plans get metadata-only detection. Scale adds custom policies, user anonymization, snippet forensics, and full audit trail.
Every tier includes optimization insights. Scale unlocks ML intelligence and governance.
Automated recommendations to reduce spend without sacrificing quality.
Four layers of privacy hardening protect sensitive data before it reaches third-party LLM APIs.
Drill into every API call with full token breakdowns, cost, latency, and provider metadata.
No proxy. No infra changes. Just wrap your existing calls.
import modelcost from openai import OpenAI # 1. Initialize modelcost.init( api_key="mc_xxx", org_id="org-123" ) # 2. Wrap your provider client client = modelcost.wrap(OpenAI()) # 3. Use as normal — costs tracked automatically response = client.chat.completions.create( model="gpt-4o", messages=[{"role": "user", "content": prompt}] )
No infrastructure changes. No proxy. Direct API calls stay direct.
Add our lightweight SDK to your project. Python, Node.js, and Java supported. One dependency, zero config files.
Add the @track decorator to existing functions. Tag with feature name and customer ID. Your code stays the same.
Configure budget caps and alert thresholds in the dashboard. Deploy. Every call is now tracked, attributed, and protected.
Starts paying for itself the moment you see your first dashboard.
For teams exploring AI cost visibility.
For teams shipping AI to production.
For companies that need predictive AI cost intelligence.
Full visibility, budget enforcement, and predictive intelligence — live in under five minutes.