Protect the systems
that create value.
Vallarium continuously improves and defends what your business runs on — the AI spend nobody owns, the agents with more access than anyone scoped, and the checkout, login and payment journeys that earn the money.
If we can’t identify at least 20% in recoverable AI spend, you pay half.
The audit guarantee — fixed scope, about ten days, read-only access only.
Digital Optimization and Defense
The path to value
Revenue travels a path.
Any step can quietly fail.
A customer becomes revenue by moving through your systems — page to login to checkout to confirmation. Value leaks wherever that path slows, breaks or gets exploited. We walk it the way your customers do, continuously, and close what leaks.
An illustration of the failure patterns we test for — not client data.
Seven steps, inspected end to end
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Performance kept honest on real hardware. Budgets for the metrics that decide whether people stay, measured on the mid-range devices your customers actually hold — and re-measured on every change, so a regression never ships quietly.
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The pages that matter, exercised continuously. Synthetic checks submit your forms, follow your critical links and hold your accessibility to standard — change detection catches what a deploy broke before your customers report it.
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We log in the way a customer does. Journey tests run the full authentication path — including OTP delivery — from the regions your customers are actually in, and raise a hand when a provider quietly degrades.
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Dependencies watched, incidents rehearsed. Endpoint and integration monitoring with sensible thresholds, so degradation is caught at the API — not in a support ticket — and there’s a plan for the day something upstream goes down.
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The money path, verified on every deploy. Continuous synthetic checkouts with realistic payloads confirm that payment, tax and confirmation still work — because these flows break silently, and every silent hour is revenue.
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Attack surface mapped and shrunk. Configuration review, third-party exposure, automated-threat controls — and for AI agents and MCP integrations, a real map of what they can touch, cut down to least privilege with the evidence kept current.
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Verified past the payment. The journey isn’t done at charge — confirmation emails, webhooks and the AI systems answering your customers are watched in production, because the promise kept is what brings people back.
The gap
The tools already exist. The operator doesn’t.
Datadog watches your systems. Portkey, LiteLLM and Langfuse can route, budget and trace every token. Lakera and Protect AI can screen your prompts. All excellent — and all idle until someone configures them for your stack, reads what they say, and acts on what they find.
Vallarium is that someone — the managed layer that audits, deploys, configures, interprets and operates. You keep the tools, the data and the leverage.
Monitoring platforms
Datadog · Catchpoint · Site24x7
They show you dashboards. Someone still has to know which number is quietly costing you money.
LLM gateways
Portkey · LiteLLM · Langfuse · Helicone
They enforce budgets and routes. Someone still has to design the routes worth enforcing.
AI security tools
Lakera · Protect AI · Prompt Security
They flag the attack. Someone still has to close the permission that let it in.
What we improve and defend
Three lines of work. One ladder of trust.
Every engagement starts small, fixed-scope and falsifiable. Confidence is earned the same way access is — one rung at a time.
AI Cost Control
The falsifiable entry point. We find the waste in your inference spend, recover it, and keep it from creeping back as models ship and features launch.
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Spend audit read-only access · about ten days
Usage exports priced route by route, the four waste patterns hunted down, and a report you can act on — with us or without us.
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Gateway implementation inside your VPC
Routing, keys, budgets, tracing and failover — the infrastructure that makes savings permanent instead of a one-time cleanup that decays.
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Managed cost ops ongoing
Re-optimization as models ship, anomaly alerts before the surprise invoice, and spend governance for every new feature.
AI-Agent & MCP Security
Your agents read, write and act. We map what they can actually touch, close the attack classes that matter, and keep the evidence current.
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Security assessment fixed scope
Real permissions, tool scopes, and the injection and poisoning surface — documented with evidence, not adjectives.
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Hardening sprint changing production behaviour
Least privilege, allowlisting, sandboxing, approval gates — and a regression suite so the hardening holds.
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Continuous assurance standing access, earned
Re-tested on every change, with audit-ready evidence for the enterprise security reviews your customers will run on you.
Revenue Journey Assurance
Checkout, payment, OTP, signup, login — the flows that earn your money break silently on every deploy. We catch it before your customers do.
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Journey audit end to end
Your critical money paths tested the way customers travel them — from the regions they actually buy from.
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Assurance retainer continuous
Synthetic journeys running around the clock, with alerting that reaches a human who acts on it.
Every engagement is fixed-scope and priced before we start. You see the full number in the proposal — never an open-ended invoice.
Under watch across every engagement
- Performance & Core Web Vitals
- Accessibility that holds
- Attack surface & configuration
- Third-party & API exposure
- Automated threats & abuse
- Regional availability
- Regression detection
- Incident readiness
How we work
Improvement isn’t a project. It’s a loop.
Your systems change with every deploy, every model release, every dependency bump, every new attacker technique. A report describes one day. A loop keeps you covered on all the others.
Discover, understand, prioritize. Improve, defend, verify. Then watch — and begin again. The loop doesn’t finish, because your systems don’t stop changing.
Proof before commitment.
“If we can’t identify at least 20% in recoverable AI spend, you pay half.”
One true finding, free
Before you pay anything: read-only access, and we come back with something specific and quantified from your own stack. Not a deck.
A fixed price, known upfront
Scoped before we start, agreed in the proposal, capped. If the recoverable spend isn’t there, half of it comes back.
The report is yours
No standing access, no lock-in. Act on it with us, or without us — it’s designed to be useful either way.
Engagements are fixed-scope with liability capped at fees paid. We reduce risk — we do not guarantee security. That sentence stays on this page because it’s true.
What changes
Outcomes you can hold us to.
- Fewer failed journeys
- Faster pages on real devices
- Earlier detection of what breaks
- Reduced exposure across agents & APIs
- More reliable transactions
- Less unplanned downtime
- Recovered AI spend, kept recovered
- Revenue that stays earned
Before / after, when it’s real
| Measure | Before | After | Verified |
|---|---|---|---|
| Checkout completion | — | — | — |
| p75 page load, mobile | — | — | — |
| Recoverable AI spend | — | — | — |
This table publishes measured, permissioned results from real engagements. It stays empty until we have numbers we can stand behind — we don’t invent proof.
Proof
We show our reasoning before anyone pays for it.
No logo wall, no borrowed trust. The method is public — read it, apply it yourself, or hold us to it.
Teardown · the method in full
Anatomy of an LLM bill: how a typical Series-A stack overspends 41% without noticing
A representative bill, walked with the exact method we run in paid audits — priced route by route, four findings, every number reproducible from exports the team already had.
- Client case studies reserved — with permission only
- Security findings resolved reserved
- Journey reliability improvements reserved
- Methodology, published in progress
Every proof item on this page will say what changed and why it mattered. Nothing appears here without the client’s permission — which is why it’s quiet for now.
Who this is for
Built for teams that feel the bill personally.
Seed → Series A, AI-native
Real money on model APIs every month. The bill grew faster than anyone planned, and it lands on a founder’s desk.
Fintech & SaaS with an LLM feature
AI bolted onto a revenue product — usually both problems at once: an unoptimized bill, and an agent with broader permissions than anyone scoped.
Teams where nobody owns AI spend
Costs sit between engineering and finance and belong to neither. Routing, caching and model choice happen ad-hoc — and the invoice shows it.
Responsible for client systems rather than your own? Agencies and platform teams — talk to us about coverage.
Engagement
Designed to be safe to start.
You shouldn’t have to trust an unfamiliar vendor. The process makes trust unnecessary at the start — and earned by the end.
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A thirty-minute call
Read-only access to your usage dashboard, or twenty minutes of screen share. That’s the whole ask.
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One finding, free
Something true, specific and quantified from your own data — before any commitment, so you can judge the work, not the pitch.
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A fixed-scope audit
About ten days, price agreed upfront, money-back-half guarantee. The report is yours either way.
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You decide what’s next
Implementation, security assessment, continuous coverage — each step earned by the last. Or stop. No lock-in.
Request a private assessment.
Tell us what you’re running and where it hurts. The first thing you get back is a finding, not a pitch.
- A reply within one business day
- Read-only access is all we ever need to start
- NDA-friendly — yours or ours
- No mailing list, no follow-up sequence
Prefer email? info@vallarium.com
Received.
Thank you — expect a reply from info@vallarium.com within one business day. If it’s urgent, email us directly and say so.