An AI budget with no defensible return. Three routing micro-agents + six hooks moved traffic to OSS models where it landed the same result.
58%monthly API cost cut
Contracted AI consulting & implementation
Real results from your AI spend.
Hire us if you want measurable movement on the metric your leadership answers for. We audit your AI spend, cut it, and ship production systems that pay for themselves — a multiple return on our fee, from lower AI spend and higher throughput.
$1.44M
annual AI API cost saved, per client
Proof, not promises
The result first. The work second.
Five outcomes from optimization and delivery work — the shape of results pending anonymized, client-verified figures. Nothing here is invented.
$1.44M
/yr AI cost saved, per client — reusable workflows + repo audits removed $120K/mo token waste
99.8%
regulatory rule compliance — a 15K-token monolith re-cut to 15 arrays + 4 routing hooks (from 64%)
99%
lower retrieval latency — a Qdrant semantic cache: 4 min cold retrieval to 3 sec
92.9%
retrieval spend cut — offloaded to Tavily / Brave: $12K/mo to under $850/mo
95%
session-dropout reduction — 60% capacity compaction saved $14.5K/mo
Pipelines that failed silently and lost revenue attribution. GOSTA + schema contracts made every stage fail loud, not silent.
$340Klead-attribution recovered
Quality regressions users could feel. A Builder–Adversary–Arbiter adversarial-QA loop hardened every release before ship.
-78%defects · -60% bug tickets
How we work
We audit before we build — and we’ll tell you not to build.
One partner from diagnosis to shipped system. Fewer handoffs, less drift, and a savings number you can put in front of the board before a line of code is written.
Audit-first
Phase 1 is an audit of your data foundation and token spend. The savings become a number before we build — not a promise after.
Vendor-neutral
If a workflow fix beats a new model, that is the recommendation. We’re paid to move your metric, not to sell a build.
Named method, verifiable delivery
SPARC, GOSTA, JTBD and Start-with-Why run every engagement, with verification gates at each stage so what ships is what was scoped.
The method, in outcomes
SPARC
GOSTA
JTBD
Start with Why
3.5 wk
faster launches — SPARC + 3 verification gates, −48% rework
$180K
maintenance saved — skill registries + pre-flight rules, −42% redundant code
Reliability by design. A Builder–Adversary–Arbiter adversarial-QA loop attacks each release before it ships — the discipline behind a −78% defect reduction.
Who we serve
From first production system to regulated scale.
The same audit-first discipline, framed for where you are — startup, SMB, or enterprise.
Control for the age of AI agents
✓Stop the budget burn. Spend ceilings, token attribution, and real-time cost visibility on every model call and agent run.
✓Govern access & keys. Inventory the credentials, tokens, and grants your AI agents hold — then retire what shouldn’t exist.
✓Tame autonomous SDLC. Guardrails on your AI coding agents so changes stay supervised, loops get caught, and failures never run silent.
A boutique path: shorter timelines, lower cost, direct principal access — Big-4 delivery discipline without the pod tax.
Engagements
Start with your biggest pain point.
Pick the entry point that matches your worst problem — not a tier off a menu. Tell us where AI is bleeding budget or stalling delivery, and we start there.
AI Cost Audit
2 weeksWe map token spend and workflow friction to a role-owned metric and hand you a defensible savings number — no build required.
You leave with
A quantified savings target and the shortest path to it.
Optimization Sprint
6 weeksWe ship the highest-ROI optimizations into your stack — reusable workflows, routing, caching, guardrails — and prove the delta.
You leave with
Shipped, measured savings running in production.
Fractional CAIO
RetainedOngoing strategy and hands-on delivery — the embedded AI leadership you can’t hire fast enough, on the metrics your board tracks.
You leave with
Sustained AI leverage without a full-time hire.
The math already favors acting.
Independent benchmarks — not our numbers. Controlling AI spend is where the return sits.
up to 60%
of inference spend recoverable by routing each call to the right-sized model — at equivalent output quality.
RouteLLM · TrueFoundry
27–40%
typical AI & cloud cost reduction once FinOps discipline is actually in place.
FinOps Foundation · CloudZero
80%+
of teams overshoot their AI & cloud budgets — most by more than a quarter.
Gartner · Mavvrik
Start here
See the return on your AI‑spend.
Tell us the KPI you’re accountable for. We’ll come back with where your AI spend is leaking value and the shortest path to fixing it. No pitch deck — a diagnosis.
1We audit where AI spend is leaking value in your workflow.
2We name the metric your role is measured on.
3We propose a 2-week audit with a defined savings number, and the ROI on our fee modeled up front.
Prefer email? Reach us directly at contact@aigrounded.com.