trAIce

Control every dollar your company spends on AI.

One operating view for product AI and employee tools. Attribute spend to customers, features, teams, and people; catch budget spikes early; and give engineering leaders the evidence to optimize.

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No credit card · open-source SDK · 5-minute install

Helpdesk AI
Dashboard
Last 30 days
Last 30 days · Team plan
Customer flipped to negative AI margin · Initech now costs $410 against $99 revenue
Daily spendUpdated now
30 days agoToday
Total spend
$3,182
30-day cost
Avg cost / call
$0.042
75,761 events
Tokens
7.8M
prompt + output
Top feature
chat-resolver
by spend
Top customer
Initech
by spend
No gateway in your request path
Open-source SDK
Prompt capture is opt-in · 14-day TTL
Product + employee spend in one workspace
The problem

AI spend is growing faster than the systems used to manage it.

Engineering sees model spend. Finance sees invoices. IT sees SaaS commitments. CTOs and VP R&D leaders still cannot point to the customer, feature, team, or employee that changed the budget.

Which customers are profitable on AI?

Your dashboard says “OpenAI: $4,012/mo.” That’s not an answer. You need cost per customer, joined to the revenue they pay.

Your bill jumps 40% and no one can explain why

A new feature? A chatty customer? A retry loop? A model you forgot to downgrade? Aggregate spend hides the leak.

Which team or employee pushed AI spend over budget?

Seat commitments, metered tools, and raw API usage land in different systems. Leaders need one team-level view and alerts before a burst becomes the monthly baseline.

The build side

What AI costs to make.

Start from your application’s context: feature, customer, and run. Do not start from a billing export. That’s the difference between “how much did the API cost” and “which feature is unprofitable.”

Per-customer AI margin

Every LLM call tagged with a tenantId, joined to the revenue that customer pays. See who’s profitable and who’s a subsidy in disguise.

Agent & workflow economics

Cost per run, per tool step, retry waste. Built for multi-step agents, not just per-call dashboards.

Cost-validated savings

We replay sampled events on cheaper models, score quality with a judge, and only recommend swaps where quality holds.

Prompt-cache savings

New

Your cache hit rate, the money it’s already saved, and where you’re leaving savings on the table. It is the one lever with zero quality tradeoff.

New
The buy side

What your team spends using AI.

Beyond what AI costs to build, see employee usage from Codex, Claude Code, and internal sources you send through the API. Compare teams day by day, combine metered usage with seat commitments, and alert when an employee crosses budget.

Internal Spend
Employee AI Spend
Track employee tool usage separately from product AI spend.
Last 35 days
Daily employee AI spendUpdated now
30 days agoToday
Usage cost
$8.7k
Token estimate
$9.1k
Monthly commitment
$4.2k
Employees
47
Billable tokens
126M
EmployeeBillable est.Token est.
Liam O'Connor
Engineering · Codex
18.4M
$684
Aisha Rahman
Data & AI · Claude Code
9.7M
$318
Maya Chen
Engineering · Codex
7.9M
$276
Liam O'Connor exceeded his $500 employee AI budget during a coding-agent spike.
Interactive demo

Three operating views in the real platform UI.

Each workspace opens with fresh fictional data, current alerts, and read-only controls.

-314%
Initech AI margin

Customer AI-margin leak

Helpdesk AI finds Initech paying starter-plan revenue while driving enterprise-grade resolver cost.

$500
monthly budget / employee

Internal AI spend abuse

Employee AI Spend shows 47 people across 10 uneven teams, with Engineering and Data & AI driving most metered usage and one engineer crossing a $500 monthly budget before optimization.

2 views
one operating workspace

Product + employee AI spend

AI Operations gives leaders one workspace for customer-facing AI economics and internal employee usage.

Control & roadmap

Detection today, control on our terms. Never a gateway.

Budgets & alertsLive
Advisory enforcement · no gatewayLive
Exact-cache enforcement · SDK-sideLive
Routing and fallback enforcementPlanned
How we fit

One platform for both sides of company AI spend.

Gateways route. Evals score. Observability traces. Spend tools count seats. None of them connect what you build to what you buy.

What you wanttrAIceAI gatewayPortkey, LiteLLMEvalsBraintrust, LangSmithObservabilityDatadog, Helicone
AI cost per customer / tenantNoNoPartial
AI gross margin (cost vs revenue)NoNoNo
Cost per agent run / tool stepPartialNoPartial
Cost-validated model swapsNoPartialNo
Prompt-cache hit rate & savingsPartialNoPartial
Employee / team AI tool spendNoNoNo
Both build-side and buy-side AI costNoNoNo

Buy-side spend tools (Torii, Zylo) and AI-FinOps (Amnic, Finout) cover half of this. None tie it back to the product you ship. See what trAIce doesn’t do →

Built for

Three people, three jobs, one platform.

CTO / VP R&D

Own the full AI operating budget.

See product economics and employee usage together, with accountable teams, active budget alerts, and a clear path from anomaly to action.

Engineering manager

Know which team, workflow, or person changed spend.

Daily team breakdowns, employee budgets, and deep-linked logs make cost reviews concrete without turning managers into billing analysts.

AI platform lead

Optimize with evidence, not blanket limits.

Trace cost to customer, feature, agent run, employee, and team. Validate model changes and apply targeted budgets where they matter.

“Provider invoices tell you how much. We built trAIce to tell you which customer, feature, and employee, so you can act before the bill arrives.”

The trAIce team

Frequently asked

Good questions, straight answers.

See where your AI budget really goes.

Open the live demo with no signup. See a customer margin leak, an employee budget spike, and a unified product + employee workspace.

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10,000 events/month free, no credit card.