MLOps & LLMOps

LLM Cost Optimization, Routing & Caching

LLM bills tend to climb faster than usage would explain, usually because every request (simple or complex) is going to the same expensive frontier model by default. This service engineers that spend down: intelligent routing that sends each request to the cheapest model capable of handling it, response caching for repeated or near-duplicate queries, and request batching where latency allows, all validated against your actual quality bar so cost drops without anyone noticing a difference in output. It's for teams whose inference spend is growing faster than their traffic, or who've never questioned whether every request needs the biggest model available. The deliverable is a routing and caching layer with measured savings attached to it, not a suggestion to try a smaller model.

This is a capability we deliver for you as a service, not a role we’re hiring for.

How We’d Approach This

A clear, staged plan, not a black box

These are the service-specific steps inside our six-step process.

1
Diagnose current token spend by request type, model, and endpoint to find where cost is concentrated and misallocated.
2
Pilot model routing and caching on the highest-volume request type, measuring quality against the existing baseline.
3
Review cost savings and quality metrics with stakeholders to confirm the quality bar holds before routing more traffic.
4
Roll out routing, caching, and batching across remaining request types, with a dashboard tracking savings over time.

What You Get

Deliverables from this engagement

Token-cost audit broken down by request type and model
Intelligent routing layer sending requests to the cheapest capable model
Response caching and request-batching implementation
Cost-savings dashboard with before/after spend comparison

Six Ways We Could Architect This

Different engagement, different build, pick the shape that fits

There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.

Read all 6 architectures as text

Lean Fast-Start Architecture

Request Intake

Incoming LLM Request
Simple Router Function

Basic Routing

Request Judged Simple or Complex
Cheaper Model Endpoint
Frontier Model Endpoint

Basic Caching

In Memory Cache Check
Response Returned to Caller

Cost Tracking

Token Usage Logged
Manual Cost Spreadsheet Updated

Cloud-Native / Managed Services Architecture

Managed Gateway Layer

Client Request
Managed API Gateway
Routing Decision Service

Model Provider Layer

Small Fast Model Endpoint
Mid Tier Model Endpoint
Frontier Model Endpoint

Managed Cache Layer

Managed Cache Service
Response Deduplication

Cost Operations

Cloud Billing Export
Cost Dashboard by Request Type
Savings Report Generated
Quality Sample Audit Log

Event-Driven & Automation-First Architecture

Triggers

Request Event Received
Router Decision Engine

Automation Layer

Cache Hit Available
Cached Response Returned Instantly
Complexity Classifier Runs
Cheapest Capable Model Selected

Batch Queue

Latency Tolerant Requests Queued
Batched Call Sent to Provider
Responses Split Back to Callers

Cost Alert Path

Real Time Spend Tracked
Cost Anomaly Detected
Auto Alert to Engineering

Enterprise-Grade & Compliance-Ready Architecture

Governance Layer

Cost Governance Policy
Data Handling Rules per Provider
Access Control for Routing Config

Secure Routing

Role Based Config Access
Redundant Multi Provider Failover
Versioned Routing Rule Store

Auditable Cost Management

Audit Log of Every Routing Decision
Compliance Review of Provider Data Handling
SLA Monitoring per Provider

Compliance Delivery

Signed Off Routing Policy
Audit Trail Export
Cost and Compliance Reporting Cadence

AI-Augmented, Human-in-the-Loop Architecture

Request Signals

Incoming Request Content
Complexity Classifier Model
Historical Quality Outcomes

AI Routing Layer

Predicted Task Complexity
Cheapest Capable Model Selected
Response Generated

Human in the Loop

Quality Sampling Review Queue
Routed Output Meets Bar
Routing Rule Flagged for Correction
Human Approved Routing Rule

Delivery

Rule Trusted at Full Scale
Savings Confirmed on Dashboard

Integration-Heavy / Ecosystem-Connected Architecture

Client Systems

Client API Gateway
Routing Integration Layer
Client Finance and Billing System
Client Observability Stack

Routing Core

Model Routing and Caching Engine
Multiple LLM Provider Accounts

Two Way Sync Layer

Client Usage Analytics Sync
Client FinOps Dashboard Sync
Internal Analytics Platform
Finance Reporting Tool

Shared Governance

Joint Review with Client Finance and Engineering
Published Cost Savings Report

Ready to get started?

Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start, scoped small enough to prove itself before you commit to anything bigger.

Talk to us about LLM Cost Optimization, Routing & Caching

Most engagements like this start as a $500–$2,500 pilot, see full pricing.