sipi.bot for LLM Application Teams
Budget controls for teams building on LLM APIs
Why llm application teams choose sipi.bot
LLM app teams need to control token costs without throttling product velocity.
Common pain points sipi.bot solves
- Token costs unpredictable per request
- Hard to attribute spend to features
- No circuit breaker for runaway agents
What llm application teams get with sipi.bot
- Feature-level cost attribution
- Automatic circuit breakers
- Budgets per agent or per workflow
How it works for llm application teams
- Sign up and configure your spend firewall settings in under 5 minutes.
- Integrate via API or use the dashboard — no engineering team required.
- Get results immediately and export in your preferred format.
Common spend patterns for LLM Application Teams
LLM Application Teams run agents that can move money in the course of their work. The exact pattern varies, but the failure modes repeat: an agent loops on a paid API call, a tool call hits the wrong merchant, a multi-step workflow accumulates charges faster than anyone expected, or a prompt injection tricks the agent into a transaction it should never have made.
A runaway agent's cost is bounded only by the limits you set before it spends. The pattern is not rare and it is not cheap.
How sipi.bot fits your workflow
sipi.bot is a spend firewall for autonomous AI agents. It sits between your agent code and your payment methods, evaluating every transaction against your rules in under 5 milliseconds and returning one of three structured decisions: approve, block, or flag. Per-transaction limits, daily ceilings, velocity caps, merchant allowlists, and human-in-the-loop escalation are all enforced before a dollar moves. Pricing starts at $99 per month.
For LLM Application Teams, the value is enforcement, not just observability. Dashboards tell you what happened after the money moved. A spend firewall stops the transaction before it moves. The difference, on a runaway loop, is the difference between a $2 anomaly and a $2,000 incident.
A typical deployment
- List the transactions your agents actually initiate — paid API calls, provisioning, purchases, refunds.
- Set a per-transaction limit that covers legitimate use but flags anything unusual. For most LLM Application Teams workflows, $1 to $5 per transaction is enough.
- Set a daily ceiling per agent ($10-$50 for development, higher for production).
- Add a velocity cap (transactions per minute) to catch loops. Ten per minute is a reasonable starting point.
- Configure a merchant allowlist so the agent can only transact with vendors you have approved.
- Turn on alerts and run a postmortem on every flagged transaction.
Why LLM Application Teams choose sipi.bot
The alternative is building this yourself: a policy engine, a decision API, an audit log, alerting, and a review workflow. That is months of engineering for a problem that is not your core product. At $99/mo, sipi.bot is cheaper than a single incident and deploys in an afternoon.