Built for the AI buildout
Token-level visibility, business-level allocation
AI bills don't tell you who used what. Provider dashboards stop at the API key. GenAI Intelligence connects every input and output token to the model that served it, the team that called it, and the product that paid for it.
What you get
From token to invoice, accounted for
The pieces FinOps teams actually need when AI spend starts mattering.
Token-in, token-out
Input, output, and cached tokens broken out per request.
Cost by model
Compare GPT-4o, Claude, Gemini, Llama side by side.
Allocate every key
Map API keys to teams, products, or customers.
Shared cost split
Distribute platform-wide AI costs using rules you control.
Anomaly detection
Catch token spikes and prompt blowouts in real time.
Signals → actions
Pause keys or swap models when usage crosses policy.
End-to-end AI cost control
Every capability your team needs to operate AI responsibly
From the first API key to enterprise-scale rollout, GenAI Intelligence covers the full lifecycle.
Provider connections
Read-only API key or billing-file ingestion. Usage flows into Cloud Intelligence within minutes. No agents, no pipelines.
Token accounting
Input, output, and cached tokens reported per request. Aggregated by model, key, user, or any custom dimension.
Multi-provider unification
One schema across OpenAI, Anthropic, Google, Bedrock, Azure OpenAI, Cohere, Mistral, and more.
Model-level cost analysis
Cost per model, per workload, per request. Find rightsizing opportunities the way you would for compute.
Allocations
Build allocations using API key, model, user, prompt metadata, or custom tags. Keep AI separate or fold it in.
Shared cost distribution
Split eval pipelines, embeddings, and internal copilots across teams with fixed, proportional, or custom logic.
Budgets and alerts
Thresholds per team, product, or model. Notifications route to Slack, email, or PagerDuty.
Anomaly detection
ML-driven detection of unusual token consumption and prompt-length blowouts. Re-notifications when spend keeps climbing.
Insights
Curated recommendations to right-size models, kill idle keys, and tighten over-permissive access.
CloudFlow automation
Turn signals into actions. Pause a key or swap to a cheaper model, no human in the loop.
Showback and chargeback
Tie AI cost to revenue, customers, or features through DataHub. Same engine as your cloud cost.
Unit economics for AI
Cost per inference, per user, per feature. Track how AI economics change as your product scales.
Integrated with your entire tech-stack
Works natively with your cloud providers, data platforms, DevOps and SecOps tooling. Custom integrations are available on request.
Explore
visibility across models/providers
AI spend allocated
spreadsheets or pivot tables
Enterprise-grade by default
Read-only access, audited controls, and the certifications procurement teams ask for.
SOC 2/3
GDPR
ISO 27001
Stop guessing what AI is costing you
Every token. Every model. Every team.
Frequently asked
questions
How does GenAI Intelligence connect to our AI providers?
Read-only API key or billing-file ingestion. No agents, no pipelines, no code changes. Token usage and cost flow into Cloud Intelligence within minutes.
Which providers are supported?
OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI, Cohere, Mistral, Databricks, and Snowflake Cortex, with more added regularly.
Can we allocate shared AI costs like eval pipelines or internal copilots?
Yes. Split platform-wide costs across teams using fixed rules, proportional usage, or custom logic you define.
Does this replace our existing cloud cost tooling?
No. AI spend folds into the same allocations, budgets, and chargeback flows you already use for AWS, GCP, and Azure in DoiT Cloud Intelligence.
How fast does anomaly detection catch a runaway prompt?
Token spikes and prompt-length blowouts are flagged in near real time, with re-notifications if the spend keeps climbing.