AI that costs more than the problem it solves isn't solving anything.
How costs are controlled
- Model routing — Tasks are matched to the cheapest model that can handle them adequately.
- Task decomposition — Complex tasks are broken into smaller pieces. Simple pieces route to cheap models; only genuinely complex pieces route to expensive ones.
- Caching — Repeated queries and common patterns are cached to avoid redundant processing.
- Local processing — Routine tasks run on local models at near-zero marginal cost.
Budget awareness
The system tracks processing costs in real time. If a task is approaching unusual cost levels, you're informed before proceeding. There are no surprise bills from runaway inference loops.
The result
You get powerful AI assistance at a predictable, flat monthly rate. The cost engineering happens behind the scenes so you can focus on your work instead of managing AI expenses.