Strategy
Find the work that is genuinely ambiguous—and stop paying a model to do the rest.
Drop your
inference
costs >70%
Talk to Our Team
The work
Strategy, guardrails, systems
Guardrails
Make policy explicit, version-controlled, and inspectable before inference has a chance to drift.
Systems
Build the routing, local infrastructure, and deterministic tools the workflow actually needs.
The cost spectrum
Route each job to the smallest useful tool.
Move predictable work out of inference. We map what needs a frontier model, what can run locally, and what should be code.
Cloud inference
Useful for difficult reasoning and broad model capability; per-call costs, output variability, and data handling need deliberate controls.
On-prem inference
Can keep model execution close to your data and model version under your control. Hardware, operations, and performance depend on the workload.
Local code
Known rules, repeatable outputs, no model inference. Code can be inspected, tested, and versioned.
Data residencyExplicit access controlsAuditable decisions
Controls are configured for your requirements.
Results
The savings are architectural.
Examples from engagements where routing, deterministic code, and appropriately sized models replaced blanket frontier inference.
01 / routingB2B content operations
−60%cost reduction+30% top-line revenue
CrowdTamers: an audit found much of the spend was structured formatting and routing work that could be expressed as deterministic code. The engagement also reported +30% top-line revenue.
02 / transformScientific computing
−99%cost per chemical analysis$5.00 → under $0.005
greenchemistry.ai: converting deterministic data transformation from frontier inference to Python reduced a run from $5.00 to under $0.005.
03 / right-sizeAI-native product
−99%cost per million words analyzedHigher accuracy / lower latency
A text-detection company moved classification to a smaller local model, reporting higher accuracy and lower latency alongside lower API spend.
A practical route
Audit. Propose. Build.
Measure before changing the architecture; put an explicit plan in front of implementation.
Audit
We map every AI call in your workflows, measure what each one costs, and score each task on a determinism scale.
Propose
We present what moves to deterministic code, what moves to a local model, and what stays on a frontier model—and why. You see before/after cost before implementation.
Build
We implement the new workflows on infrastructure you control. A third-party API remains only where it genuinely has to.
WISDOM OF THE CROWDS
Useful patterns, stated in public
These are attributed public posts, not customer reviews or endorsements. They provide independent commentary on routing, controls, and deterministic work.
Most people building AI agents obsess over which model to use. The model is the easy part. Routing is what actually kills you in production.Read original post ↗
The worst agentic systems I've seen have one thing in common: they use an LLM for everything. Date parsing. Math. Format validation. Lookups. Transformations.Read original post ↗
Let the LLM do what it's good at — reasoning, pattern recognition, extraction. But when it comes to the governance decision — that decision gets made by explicit, version-controlled, inspectable code.Read original post ↗
“Not everything needs an LLM. Sometimes the boring solution is the profitable one.”Read original post ↗
“Prompts get you the demo. The harness gets you through month two.”Read original post ↗
“The best way to enforce rules is with external tools that communicate failure to the AI.”Read original post ↗
It's transformational for back office, for rote tasks, for boring, for B2B — data cleansing, swivel chair processes.Read original post ↗
“For anything specific and numerical it will always be cheaper and more reliable to just write normal deterministic software.”Read original post ↗
Public posts reproduced with attribution. Links lead to the original posts; they are commentary, not endorsements.
Start with the bill
Spending $10,000+/month on AI? We should talk.
If the bill is at that level, there is likely meaningful waste to find. The audit is free.