FinLLMOps & Cost Governance

Real-time token budgeting, semantic caching, and task-specific model routing that cuts LLM operational spend by 40-70% without sacrificing accuracy.

check_circleIntelligent multi-tier model routing between frontier models and compact SLMs

check_circleSemantic vector caching that eliminates redundant frontier-model calls

check_circleReal-time token budgeting and spend alerting tied to business KPIs, not just token counts

The problem with uncapped LLM spend

Unmanaged agentic systems burn tens of thousands per month in brute-force frontier-model calls with zero semantic caching. We install FinLLMOps discipline — the same operational rigor FinOps brought to cloud spend — directly into your agentic infrastructure.

What’s included

Task-specific SLM routing that reserves frontier models for the calls that actually need them
Semantic caching layers that cut recurring inference expense by up to 68%
Real-time budgeting dashboards so cost governance is visible before the invoice arrives

How We Work

Step 1

Spend Audit

We trace every LLM call in your current stack and identify uncapped token bleed.

Step 2

Routing Design

Task-specific SLM routing and semantic caching are layered in without touching output quality.

Step 3

Budget Guardrails

Real-time token budgets and fallback policies are wired into your existing observability stack.

Step 4

Continuous Optimization

Ongoing model routing tuning as new frontier and open-weight models become cost-competitive.

Ready to discuss finllmops & cost governance?

Book Technical Discovery Audit