Good fit
- AI or agent systems touching spend, customer answers, memory, or ops workflows.
- You can share architecture, traces, prompts, policies, or failure examples under scope.
- You want a diagnostic, one focused fix, or a larger implementation.
Dhavan Shah
I help B2B software teams diagnose and fix unreliable, costly, or hard-to-control AI workflows—through fixed-scope diagnostics, sprints, and implementations.
UZH MSc · Kaggle Top 0.5% · Former Applied AI @ DevRev · Founder, KazenAI
Three fixed-scope engagements. Prices in USD. Remote. Written deliverables—not open-ended billing. Pick the offer that fits, or describe the problem if you are unsure. Next step: send a short brief.
From $5,000 · 1–2 weeks
A focused review of one production problem. I trace what is going wrong, why it matters, and what I would change. You get written findings, priorities, and a walkthrough.
From $18,000 · 4–8 weeks
Fix one important production AI problem end to end. Typical work includes agent controls, cost enforcement, evals, grounding, workflow reliability, or failure recovery.
From $40,000 · typically $75,000–$100,000+
Larger systems work spanning multiple workflows, integrations, or longer production ownership. Scope and price confirmed after the problem call.
If you have a recurring production AI problem that doesn’t fit neatly above, send a short description.
These are independent options. Most teams start with a Diagnostic or Sprint. A Sprint can start without a Diagnostic when the problem and owner are already clear.
From $3,000/mo after a Diagnostic, Sprint, or Implementation—when continuing reliability work is still useful. One focused track per month, not full-time embedding.
Fit check
Strongest fit: production or near-production system, a technical owner, and enough signal to investigate.
What you do next
Clear sequence. No obligation until you choose a scoped engagement.
Short, non-confidential description of the system and what is going wrong. I reply within one business day.
Required first step30 minutes on what is failing, what you have tried, and what it is costing you.
If there is a fitDiagnostic, Sprint, Implementation—or I tell you I am not the right fit.
Scoped deliveryAgree what changed. Continue only if there is continuing value.
OptionalReady to start?
Prefer email for a short intro, or if your company blocks web forms.
Systems I built to show the technical depth behind my consulting work—not client case studies. Agent FinOps + Agent Lens are KazenAI’s current product focus; Agent Brain is a future direction.
Evaluating Agent FinOps + Agent Lens as a product? Request a demo on kazenai.com →
Why teams trust this work
I am an independent AI Systems Engineer. I diagnose and fix hard production AI problems around reliability, cost, evaluation, permissions, and agent control. I am also the founder of KazenAI, a separate product company building Agent FinOps and Agent Lens for teams operating customer-facing AI workflows.
Previously at DevRev, I shipped LLM systems across live customer workflows. My broader experience includes applied AI work with AXA XL and Sulzer in Zurich, an MSc in Data Science from the University of Zurich, and Kaggle Competition Expert, ranked in the global top 0.5%.
My consulting work is fixed-scope: Diagnostic, Sprint, Implementation, and occasional Reliability Partner tracks. KazenAI is a separate product business with its own product scope, hosted demo, and public Python packages. A consulting engagement does not require adopting KazenAI, and client code, systems, and confidential data remain isolated under the engagement agreement.
This form is for consulting enquiries. Describe the system and what is going wrong—non-confidential only. I reply within one business day. If there is a fit, I send a private link for a 30-minute problem call. This is not a purchase or booking.
Looking for the KazenAI product? Request an Agent FinOps + Agent Lens demo on kazenai.com.
Prefer email? [email protected]