Taha Bagatur

From AI demo to reliable production.

I help small product teams and agencies run AI features that are fast, measurable and affordable, and keep the infrastructure underneath them healthy. Fixed prices, read-only first, no long contracts.

Email me a problem See a sample report

AI in production

For teams that have shipped an LLM, RAG or agent feature and now need it to behave in production.

Start here

AI Production Readiness Review

3-day review of one AI feature: tracing, evaluation and release gates, latency, fallbacks, cost per answer, privacy and prompt injection, retrieval pipeline. Measured findings and a 30-day plan.

$900 fixed

LLM Cost Check

Where your LLM spend goes and how to cut it: context size, model per step, caching, provider settings, and a self-hosting break-even estimate (vLLM, open-weight models).

$750 fixed

AI Deploy Fix

One specific problem: slow or failing answers, timeouts and rate limits, GPU or container issues, a deployment that won’t go live.

$250–400 fixed

AI Ops Care

Monthly cost and quality review, evaluation runs before releases, provider and model updates, small fixes.

$600–1,200 / month

DevOps & infrastructure

For teams and agencies without a DevOps person of their own.

Deployment Fix

A broken pipeline, 502s after deploys, SSL, Docker or NGINX issues, a server you are afraid to touch.

$150–300 fixed

DevOps Health Check

3-day review of one application: CI/CD, backups and restore test, monitoring, server security, secrets, cost.

$750 fixed

DevOps Maturity Assessment

Whole platform: delivery, infrastructure as code, observability, security, backup and DR. Maturity score per area and a 90-day roadmap.

from $1,750

DevOps Care

Monitoring and alert triage, patching, monthly restore test, small fixes, monthly report.

$400–800 / month

Sample reports

Fictional companies, real format. This is what you receive at the end of a review.

AI Production Readiness Review

A RAG support assistant: tracing, evaluation, latency, cost and privacy findings with a 30-day plan.

Open PDF · 4 pages

DevOps Health Check

A Laravel app on a single VPS: backups, alerting, deploys, access and cost.

Open PDF · 4 pages

Services & terms

All services, how I work, and payment terms on one page.

Open PDF · 1 page

About

I’m Taha Bagatur, an AI infrastructure and DevOps engineer. In my day job I run LLM and computer-vision workloads in production for a large retail group: GPU inference servers, RAG services, an edge fleet of 50+ devices, monitoring and drift detection. I also own the DevOps platform underneath: CI/CD, Linux servers, Kubernetes, observability and backups.

Alongside that, I take a small number of fixed-price projects for remote teams.

How I work

  • Read-only first. Reviews never change your systems; fixes happen only after written approval.
  • Evidence, not opinions. Every finding says what was measured, so your team can check it.
  • Your data stays yours. Personal data is masked in anything I keep, and access is removed when we finish.
  • Agencies: I work behind the scenes; you keep the client relationship.

Contact

Send the problem: an error, a trace, a log or a short description. Within 24 hours you get a fixed price and how I would approach it. Nothing is billed until you approve the quote.

[email protected]

Code and labs: github.com/mtbagatur