AI cost, in context
The invoice does not say why
Provider bills show totals per model. They do not show which agent looped, which customer drove the spike or whether the extra spend improved anything.
Spend tied to the work that caused it
Token counts and cost are recorded on every model call, so you can break spend down by agent, session, user or feature and compare it with eval scores and outcomes.
Record tokens on each call, group spend the way your business is organized, and check quality before you cut.
Measure
Capture token usage, model calls, retries, cache behavior, latency, and provider cost.
Attribute
Tie spend to agents, workflows, tools, customers, teams, releases, and business outcomes.
Detect
Find escalation loops, expensive prompts, inefficient tools, and model choices that changed spend.
Optimize
Prioritize changes that reduce cost while preserving quality, latency, and conversion outcomes.
What teams can do
- Attribute cost to sessions, agents, models, tools, users, workflows, and teams
- Detect retry loops, escalations, high-latency calls, and inefficient prompts
- Compare cost against quality, customer value, and business KPIs
- Route cost anomalies to the owners who can fix them
Can Anosys show which workflow is driving spend?
Yes. Anosys can attribute model and token costs to workflows, agents, tools, teams, users, and outcomes.
Can cost be linked to quality?
Yes. Cost signals can be correlated with eval scores, latency, user behavior, and business KPIs.