Private BetaBetaNow accepting cohort 02 · 2026Cohort 02 · 2026

Make your AI
agent profitable.

AI is getting more expensive. Agents still hallucinate. Profitable AI is the cost and accuracy layer for builders turning AI agents from demos into products people pay for.

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Scenarios
Growth
High
Storage Tier Distribution
75% Hot
25% Cold
ProfitableAI Suggests
AWS
Suggested
$322K
Google
$343K
Azure
$357K
Your Savings
First Year Potential
$83,121
5 Year Potential
$328,121
Growth · High breakdown
Year Cost$322 K
Total Cost39.81 PB
5 Year Cost$725 K
Growth Rate20% / Year
The Architect — chat in, get plans out.
Supported vendors
AI cost tracking across storage, compute, and tokens on these clouds, plus LangFuse.
Amazon Web ServicesMicrosoft AzureGoogle CloudOracle Cloud InfrastructureWasabi
Why now

The cost of running AI blind.
And shipping it broken.

AI subsidies are ending. Model prices are climbing. Most teams are flying without a meter.

AI infra spend
$700B+

Projected AI infrastructure spend by 2030. Most teams have no idea where their share goes.

Wasted
30%

Of cloud spend lost to idle compute, oversized storage, and model overkill.

Production gap
40%+

Of AI-generated code fails in production. Hallucinations get expensive at scale.

Plan · Monitor · Optimize

The cost and accuracy
layer for AI agents.

Real-time visibility into storage, compute, and tokens. Plan before you ship, watch the bill in flight, act on what you find.

01 · Monitor

Watch your AI spend in real time.

Track every dollar across storage, compute, and tokens. AWS, LangFuse, and your cloud stack stream into one view of what your agent costs to run.

AI spend · last 90d−$108,402
beforeoptimized
02 · Plan

Model the cost before you ship.

Compare storage tiers, model choices, and architecture options. See the unit economics for each path before you commit.

A · status quoAll-Bedrock
Opus 4.7$1.61Mper year
B · recommendedHybrid
Sonnet + QwenSAVE $487K$1.12Mper year
C · max savingsSelf-host
DeepSeek V4$0.94Mper year
03 · Trust

Plug in your stack. See cost and quality.

Pull in AWS, CoreWeave, and LangFuse. Cost and quality signals side by side. Hallucination detection and eval scoring are on the roadmap.

Bedrockusage logs · 90d
LangFuse14 agents in prod
Voice“Forecast Q3 if we move reranker to Haiku 4.5”
CoreWeave8× B200 · live
TextGoal: $0.04 per agent run
Live KPIs
$/agent run$0.038
Tokens/user/day14.2k
Cache hit rate67%
Hallucination rate2.1%
04 · Optimize

Insights into action.

Recommendations land as Terraform PRs, Jira tickets, and IaC changes. Auto-apply or review, your call.

PRroute reranker · Sonnet 4.6 → Haiku 4.5−$8.4k/mo
JIRAAGENT-2204 · semantic cache for top 10% prompts−$31k/yr
TFCoreWeave B200 pool · scale down nights/weekends−$2.1k/mo
TFs3 lifecycle rules · 37 buckets−$14k/yr
Private beta · cohort 02

Sign up for
the private beta.

Get the cost layer for your AI agent before anyone else. Cohort 02 is hands-on. We onboard every customer personally.

01
Founding-customer pricing locked in for the life of your account.
02
Hands-on onboarding from our team with a direct line to the founders.
03
Shape the roadmap. Your AI workload informs what we build next.
04
Unit-economics from day one across storage, compute, and tokens. Know your costs before the bill arrives.
Request beta
access
14 / 50seats left

We'll be in touch within 1 business day. Your data is never shared and our AI can operate on encrypted information.

FAQ

Questions,
answered.

What does Profitable AI do?
Profitable AI is the cost and accuracy layer for AI agents. We help builders monitor what their agent costs to run across storage, compute, and tokens, and we're building the layer that ensures agents work reliably in production. Plan, Monitor, and Optimize is in private beta.
Who is Profitable AI for?
Founders and engineers shipping AI agents who need to know what their agent costs and how to keep unit economics healthy as model prices climb.
What is an AI agent?
An AI agent is an app where AI does real work: calls models, uses tools, runs workflows, talks to other agents. The economics get hard fast because every interaction touches inference, storage, and tool calls, and you pay for every retry.
How is this different from FinOps or LLM observability tools?
They each see half the picture. FinOps tools (Datadog, Vantage) watch the cloud bill, not your reranker burning 60% of it. Observability tools (LangFuse, Helicone) trace agent calls, not their dollar impact. Profitable AI lives in the seam, mapping every agent decision to cost across tokens, compute, and storage.
Why now? Isn't AI getting cheaper?
The opposite. Frontier model prices are climbing and vendor subsidies are running out. Apps profitable on free credits today won't survive next year's bill. The teams that win the next 24 months will be the ones who can answer 'what does this cost per user' without guessing.
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