Four ways teams put MetricAI to work
Concrete problems we were built to solve. Every one of them starts the same way: an observability dashboard can show you what an agent spent after the fact. MetricAI sits inside the request path itself, so it can enforce a budget, detect an outcome, and settle the bill, not just report on it.
Charge customers for AI usage without guesswork.
You sell an AI product on seats or credits, but your provider invoice arrives weeks later and never maps cleanly to a customer. Margin per account is a spreadsheet exercise, and if you want to charge for a result instead of raw tokens, you're building that rules engine yourself.
Every call is attributed to a customer, workspace, and feature the moment it happens. Bill by usage, by outcome such as a confirmed booking or a resolved ticket, or a hybrid of both. Settlement runs natively in INR over UPI through Razorpay, so collecting from your customer isn't a separate integration you have to build.
- Per-customer cost and margin available the same day
- Outcome-based billing built in, charge for a result, not just a token count
- UPI-native settlement, no separate payment stack to wire up
Stop a runaway agent before it becomes an invoice.
Autonomous agents loop. A single misbehaving plan can burn through a month of budget overnight, and an observability dashboard tells you about it only after the provider has already billed you for it.
Budgets are enforced at the metering layer itself, per agent, per user, and per workspace, because MetricAI sits inside the request path rather than watching it from the side. Thresholds raise alerts. Hard caps refuse the call before the provider ever charges for it.
- Hard and soft budget caps scoped to agent or tenant
- Enforcement happens in the proxy, not in a dashboard you have to be watching
- Session-level traces showing exactly where spend went
Meter audio minutes, tokens, and tool calls as one session.
A voice agent spans speech-to-text, an LLM, text-to-speech, and tool calls across three vendors, each billing in a different unit, so the true cost of a single conversation is unknowable until you build a reconciliation script for each one.
Sessions stitch every modality into a single billable unit. Audio seconds, tokens, and tool invocations roll up to one conversation cost, with the underlying vendor-by-vendor breakdown still intact if you need it.
- Cost per conversation, not cost per vendor
- Streaming-safe metering that survives partial responses
- Latency and spend correlated on the same timeline
One ledger across every model you route to.
You route across several providers for price, latency, and availability. Every console shows its own slice, and a dashboard can line those slices up side by side, but none of them can act on what they show, and a pricing change on any one provider silently breaks your internal estimates.
One SDK captures usage regardless of destination and normalizes it into a shared unit model, backed by a maintained price book. Because the same layer that meters usage also enforces budgets and bills your customers, your routing decisions, your cost estimates, and your customer invoices never drift out of sync with each other.
- Apples-to-apples cost comparison across providers
- Routing decisions backed by your own usage data, not vendor-reported estimates
- The same ledger that powers routing also reconciles your customer invoices, instead of N separate dashboards
Not sure which one you are?
Most teams start with one and grow into the rest. Talk it through with us.