Layer 2 · Enterprise

I build your company's AI infrastructure.

From data pipeline setup to domain-specific model development, from team training to AI integration in your existing product, consulting and development from a single source. Single-source execution: the person who makes the decision is the same one who writes the code.

Work Examples

Examples from developed systems.

The following are examples from the product and research systems developed by lead consultant Burak Serteser. The same data and AI engineering expertise is applied to your enterprise projects.

End-to-end AI imaging system

A browser-based image analysis platform: data pipeline, deep learning-based automatic segmentation, cloud model deployment, and client-side inference. A single flow from raw data input to 3D output.

nnU-NetCloud RunDICOMClient-side

KVKK-compliant dataset curation

Anonymization of raw data, ground-truth labeling, harmonization, and conversion into a model-ready dataset. Clean, traceable data for training and validation.

AnonymizationGround-truthHarmonization

Data pipeline and ETL architecture

Automatic, reproducible transformation from scattered raw data (DICOM, Excel, record systems) into a research-ready and production-ready structure. Version-controlled and auditable.

ETLPipelineVersion control

Packages

5 core packages, flexible scope.

All prices are in USD and are presented in TL at the proposal stage using the Central Bank exchange rate. Scope is customized to your needs.

Package P1

Data Consulting

3-8 weeks

We build your company's data pipeline from scratch. Which data should be collected, how it should be cleaned, which metrics should be tracked, how often reporting should happen; we make your decision-making processes data-driven.

  • ·Current data inventory and gap analysis
  • ·Pipeline architecture (ETL, warehouse, BI layer)
  • ·Quality control and version control protocol
  • ·Executive summary report + implementation roadmap

Range

Scoped on a call

Request a quote →

Package P2

Workflow & Workshop

1-3 weeks

A customized workshop for your team to integrate artificial intelligence tools into their daily workflow. We map out the use cases together, then operationalize them through hands-on sessions.

  • ·Current workflow analysis (1 week prior)
  • ·Half-day or full-day on-site / online workshop
  • ·Use-case guides (PDF + video)
  • ·30-day follow-up + Q&A access

Range

Scoped on a call

Request a quote →

Package P3

Artificial Intelligence Tool Training

4 weeks

Structured training for ChatGPT, Claude, Perplexity, Gemini, and artificial intelligence tools specific to your field. Prompt engineering, model selection, cost optimization, and verification methods.

  • ·4 sessions, each 90 minutes (live)
  • ·Industry-specific prompt library
  • ·Comparative tool benchmark document
  • ·Recording access (unlimited)

Range

Scoped on a call

Request a quote →

Package P4

Custom Model Development

6-12 weeks

We fine-tune open-source models on your data, or develop domain-specific custom models. Image, text, or tabular data; classification, segmentation, regression, generation.

  • ·Data preprocessing and labeling protocol
  • ·Model selection and architecture decision
  • ·Training + validation + reporting
  • ·Production-ready model artifact (ONNX / PyTorch)

Range

Scoped on a call

Request a quote →

Package P5

Web and Application AI Integration

4-10 weeks

Integration of artificial intelligence features into your existing website or application: chatbot, smart search, automatic summarization, personalized recommendations, document analysis. API-based or self-hosted.

  • ·Use-case and architecture design
  • ·API integration (OpenAI, Anthropic, Cohere) or self-hosted setup
  • ·Frontend / backend connection
  • ·Auth, rate-limiting, logging, cost monitoring

Range

Scoped on a call

Request a quote →

Combined Package · P4 + P5

Custom Model + Web Integration Package

An end-to-end package where P4 and P5 run together. The model trained on your data connects live directly to your web or application, including API, auth, and deployment.

Planned as a single package; more efficient than running them separately.

Range

Scoped on a call

10-16 weeks

Hourly

One-time consulting

Hourly support for a specific decision, a quick architecture review, or out-of-scope questions.

Scoped on a call

Monthly Retainer

Continuous access

A fixed monthly hour package, priority response time, and a fixed retainer fee. For long-term collaborations.

Determined by consultation

Working Model

Transparent process, git-based delivery.

I write the code in your repo, deploy to your infrastructure, and IP is fully transferred at final payment. AI-assisted development is explicitly stated in the contract.

01

Repo and IP

  • ·We join your GitHub or GitLab repo as a collaborator
  • ·Full IP transfer with final payment
  • ·AI-assisted development disclosed in the contract
  • ·NDA + KVKK compliance standard

02

Development flow

  • ·staging + main branch, PR review flow
  • ·Preview URL on every PR (Vercel or Netlify)
  • ·1-2 week milestones, sprint demos
  • ·Linear / Notion / GitHub Issues open access

03

Deploy and cutover

  • ·Production on your infrastructure (Vercel / AWS / GCP)
  • ·API keys in your account, cost control belongs to you
  • ·Smoke test + handoff document on cutover day
  • ·DNS and credential transfer in one day

04

Post-delivery

  • ·30-90 day optional retainer / SLA
  • ·Bug-fix guarantee for a defined period
  • ·Training session + runbook delivery
  • ·Anonymous portfolio reference right (optional)

Is self-hosted or on-prem required? For KVKK-heavy or regulation-restricted work, delivery as a Docker / ONNX package is available. You run the model on your own server; the source code and model artifacts remain in your hands.

First Step

Let's clarify the scope first.

In a 15-minute introductory call, I listen to the current situation and the goal, then send a written proposal.