SpendTensor is the AI cost optimization platform that gives teams complete visibility, intelligent routing, and automated savings across every LLM provider.
By the time the invoice lands, the overspend is already history. These are the gaps we see teams hit once AI usage scales.
A provider invoice shows one total. Most teams cannot say which feature, team, or customer drove the bill.
Sending every prompt to a frontier model when a mid-tier model would do the job is the most common source of waste.
Without caching, batching, and prompt compression, the same tokens get paid for more than once.
Most teams cannot say where the bulk of their AI spend goes. SpendTensor traces every request — from the SDK call to the final token — so you can attribute every cent to a feature, a customer, a team.
Six surfaces. One control plane.
See every dollar across every provider in one dashboard. Attribute spend to teams, features, and customers with token-level accuracy — no more invoice mysteries.
Our engine continuously analyzes your traffic and surfaces specific, high-ROI actions: swap models, enable caching, compress prompts. Each recommendation includes projected savings.
Automatically send each prompt to the optimal model. Maintain quality with real-time benchmarking, and route only when output quality clears the threshold you set.
Set hard spending caps per team, app, or environment. Get early warnings before budgets blow. Auto-throttle gracefully instead of shutting down at midnight.
Enable semantic caching and intelligent batching with zero code changes. Stop paying twice for the same tokens and prompts.
Project next month's AI bill from your own usage history, with alerts before pricing tier jumps, runaway workloads, or anomalous spikes derail your budget.
Built for the teams that own AI spend — engineering, FinOps, and finance working from the same numbers.
Route requests through our proxy and keep the response path yours. Your users should not notice the extra hop — your finance team notices the difference immediately.
One line of code. Change your base URL. That's it. Every framework, every SDK, every provider — instantly instrumented without touching your application logic.
Never get surprised by an invoice again. Projections are built from your own usage history and shown with the assumptions behind them — so you can budget and brief the board.
Metadata-only storage by default, provider keys encrypted at rest, and row-level security that scopes every record to its own organization.
Three jobs to be done, one platform that delivers.
Slide your monthly AI bill and choose an assumed reduction. This is arithmetic on your own inputs, not a forecast of your results — see our Disclaimer.
Drop in our proxy SDK or point your gateway at our endpoint. Zero code rewrites.
We trace every request — provider, model, prompt fingerprint, tokens, latency, retries.
Get prioritized recommendations and turn on routing rules with one click. Roll back instantly.
import OpenAI from "openai";
const openai = new OpenAI({
baseURL: "https://api.spendtensor.io/v1", // ← one line
apiKey: process.env.OPENAI_API_KEY,
});
// That's it. Every request is now traced, routed, and optimized.
await openai.chat.completions.create({
model: "gpt-4o",
messages: [{ role: "user", content: "Save me money." }],
});Metadata-only storage by default, provider keys encrypted before they reach the database, and row-level security that scopes every record to the organization that owns it.
No invented benchmarks here. Each lever is something you can turn on in the dashboard and watch move against your own provider invoice.
Send classification, extraction, and summarization prompts to a mid-tier model, gated by your own quality threshold.
Semantic caching answers near-identical prompts from cache, so the same work is not billed twice.
Trim redundant context, examples, and history before they are sent upstream.
Hard limits and early warnings per team, app, or environment stop overspend before it reaches the invoice.
Connect one provider and SpendTensor shows you what that provider's own dashboard cannot: cost per feature, per team, and per customer, with the recommendations ranked by what they would save you.
Every plan includes the full optimization engine. Pay only when we save you more than we cost.
Don't see yours? Email us at cyberprosoftware@gmail.com.