Data pipeline, model selection, fine-tuning, MLOps deployment, monitoring · we are not talking about just saying "let's add AI", but about building a real production AI project. Our starting point in AI development services is simple: there is a big difference between using an off-the-shelf model and a system built specifically for your business.
6-16 weeks
Timeline
Per project
Format
Vendor-agnostic
Stack
- 01
Someone said "let's add AI too", but which business problem AI should solve was never written down; everyone understands something different.
- 02
The AI pilot you tried never left the demo stage; it never touched production, real customers or real data.
- 03
The team uses ChatGPT however they see fit; company data leaves the building uncontrolled.
- 04
Repetitive writing tasks like emails, quotes, content and summaries eat up your team's hours.
- 05
There is a chatbot or agent idea, but you fear it will give wrong answers and cost you customers.
- 06
It's unclear where the data lives; KVKK (Turkish data protection law) and industry regulations stall every AI idea at the table.
A single line: the flow that leaves the data sources comes down to production through preparation, model selection, fine-tune and MLOps. The pipeline alongside shows where each step stands.
AI pipeline
From data to production
- From business problem to AI solution.
- Collection, cleaning, labeling.
- GPT-4, Claude, Llama, custom.
- Domain-specific improvement.
- Production infrastructure.
- Hallucination, latency, cost.
Business problem definition, data availability, success metric, ROI calculation. PoC feasibility report.
Prototype model with limited data. Performance and feasibility testing.
Model training/fine-tuning with full data, MLOps infrastructure, API development.
Security, hallucination and prompt injection testing. User training also starts at this stage. The quality gate.
Traffic moves to 10%, then 50%, then 100%. The monitoring dashboard goes live.
Not pilot demos. We build real production systems. If you need a structure that decides and takes action, we handle it on the agentic artificial intelligence side; if you need text and content production, on the generative artificial intelligence side.
- 01
Use Case Definition
From business problem to AI solution.
Which problem in your business process can AI solve, what data is needed, what the success criteria are · in writing. We start from concrete scenarios like appointment classification, product recommendation engines, call analysis and automated email replies.
- 02
Data Preparation
Collection, cleaning, labeling.
Mapping data sources, filling missing data, cleaning anomalies, and labeling where needed.
- 03
Model Selection
GPT-4, Claude, Llama, custom.
Closed API (OpenAI, Anthropic) or open model (Llama, Mistral), depending on the need. Cost/performance tradeoff analysis.
- 04
Fine-tuning
Domain-specific improvement.
Model fine-tuning with company data (LoRA, RAG, prompt engineering). No vendor lock-in.
- 05
MLOps Deployment
Production infrastructure.
API endpoint, scaling, caching, fallback, error handling. On Cloudflare Workers / AWS / GCP. Fully integrated with Zoho CRM, RPA and your other business systems.
- 06
Monitoring
Hallucination, latency, cost.
Response quality, latency and cost tracking. Drift detection and a manual review queue.
1
Live training
At the same table as your team in Istanbul, remotely in other cities and abroad; with real data.
2
Full documentation
Every structure we build is in your hands, in writing.
3
How-to videos
Watch-and-apply recordings for every screen.
4
Fast support
Quick answers to anything left unclear after training.
5
Adoption report
Is the team actually using the system? We measure it.
Every company whose setup we did gets base support through three channels after go-live; it is part of our responsibility and is not priced separately. The WhatsApp channel and phone stay open for as long as we are your partner; feature and customization requests by email in the first 6 months are part of the setup, while new modules and integrations are priced separately.
01 · Email
Feature and customization requests
First 6 months after go-live, for your existing setup. Write to us; the request is logged and planned.
02 · WhatsApp channel
Team questions and instant fixes
A channel set up for your company, open for as long as we are your partner. Your team asks, small fixes happen on the spot.
03 · Phone
Urgent issues and management questions
Open for as long as we are your partner. When something stops work or management needs an answer, call us directly.
Coverage
WhatsApp channel and phone
Email · features and customization
After go-live, for every company whose setup we did. None of the three channels is priced separately; the 6-month scope covers feature and customization requests.
We build it, improve it, keep it alive.
Our AI development services deliver technical development together with process consulting; hands-on project experience with GPT, LLM and NLP systems stands behind every setup. No system survives without someone standing behind it. We stay with every system we build after delivery: monitoring, fine-tuning, and making sure your team truly adopts it.
More questions? Write to us · we reply within 24 hours.
It depends on the use case · Claude Haiku / GPT-4 mini for simple tasks, Claude Sonnet/Opus / GPT-4.5 for complex ones. If cost is critical, open models (Llama, Mistral).
30+
projects
99%
client satisfaction
3 channels
post-implementation support
We prepare a concrete proposal and a live demo based on your current system, your goals, and your timeline. No commitment before the contract.