Artificial Intelligence Development Services · End-to-End AI Projects
Full-stack AI project · from data to production.
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.
If you’re on this page, one of these is probably happening.
- Someone said "let's add AI too", but which business problem AI should solve was never written down; everyone understands something different.
- The AI pilot you tried never left the demo stage; it never touched production, real customers or real data.
- The team uses ChatGPT however they see fit; company data leaves the building uncontrolled.
- Repetitive writing tasks like emails, quotes, content and summaries eat up your team's hours.
- There is a chatbot or agent idea, but you fear it will give wrong answers and cost you customers.
- It's unclear where the data lives; KVKK and industry regulations stall every AI idea at the table.
To production in 5 steps.
- 1
Weeks 1-2 · DiscoveryUse case and data analysis
Business problem definition, data availability, success metric, ROI calculation. PoC feasibility report.
- 2
Weeks 3-4 · PoCRapid prototype
Prototype model with limited data. Performance and feasibility testing.
- 3
Weeks 5-10 · DevelopmentProduction model
Model training/fine-tuning with full data, MLOps infrastructure, API development.
- 4
Weeks 11-12 · TestingEdge case + adversarial testing
Security, hallucination and prompt injection testing. User training also starts at this stage. The quality gate.
- 5
Weeks 13-16 · DeployPhased go-live
10% → 50% → 100% traffic. The monitoring dashboard goes live.
Full-stack AI project · from data to production.
Not pilot demos. We build real production systems.
- Use Case DefinitionBusiness problem → 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.
- Data PreparationCollection, cleaning, labeling. Mapping data sources, filling missing data, cleaning anomalies, and labeling where needed.
- Model SelectionGPT-4, Claude, Llama, custom. Closed API (OpenAI, Anthropic) or open model (Llama, Mistral), depending on the need. Cost/performance tradeoff analysis.
- Fine-tuningDomain-specific improvement. Model fine-tuning with company data (LoRA, RAG, prompt engineering). No vendor lock-in.
- MLOps DeploymentProduction infrastructure. API endpoint, scaling, caching, fallback, error handling. On Cloudflare Workers / AWS / GCP. Fully integrated with Zoho CRM, RPA and your other business systems.
- MonitoringHallucination, latency, cost. Response quality, latency and cost tracking. Drift detection and a manual review queue.
Our standard in every custom implementation.
- On-site trainingAt the same table as your team, with real data.
- Full documentationEvery structure we build is in your hands, in writing.
- How-to videosWatch-and-apply recordings for every screen.
- Fast supportQuick answers to anything left unclear after training.
- Adoption reportIs the team actually using the system? We measure it.
We don't sell hours, we build systems.
We build it, improve it, keep it alive.
We 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.
Common questions.
More questions? Write to us · we reply within 24 hours.
Which LLM do you use?
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).
Does my data stay in Türkiye?
We design the solution around your data residency preference. On-premise / EU-region deployment is possible with open models. There is a dedicated section for KVKK compliance.
How much does it cost?
Monthly API cost depends on the use case (query volume × tokens). It varies with scope and the number of integrations. We produce a concrete estimate during the PoC phase.
What happens if the AI project fails?
Unsuccessful results surface in the PoC phase, before full development begins. Technical feasibility is proven in the PoC, then the investment is made · risk minimized.
Who will maintain the project?
Three options: (1) a monthly MLOps & maintenance agreement with us, (2) handover to your internal team + training, (3) hybrid. The choice is made at project start and reflected in the contract.
Are you Zoho's office or branch in Türkiye?
No; Eksenium is not Zoho's Türkiye office or branch, but one of Zoho's Authorized Partners in Türkiye. Zoho has no official office in Türkiye; the company runs its licensing, implementation, customization, and support operations through these authorized partners. We deliver that service in the local language, in compliance with KVKK, and with on-site support.
What do artificial intelligence development services cover?
We build end-to-end AI projects, from data collection and cleaning to model training, testing, deployment and maintenance. We focus on areas such as machine learning, natural language processing (NLP) and computer vision.
Which industries do you build AI solutions for?
We build tailored solutions for a wide range of industries including healthcare, finance, retail, customer service, manufacturing and education. We create algorithms specific to each industry's needs.
Do you build custom AI solutions for organizations?
Yes. We build models tailored to your own data, processes and goals. Instead of off-the-shelf solutions, we design original AI architectures.
How is data privacy ensured in AI projects?
All projects apply KVKK and GDPR compliant data management. Where needed, training is done on anonymized data, and an NDA is signed for every engagement.
Which technologies and libraries do you work with?
We develop with current AI libraries such as Python, TensorFlow, PyTorch, OpenAI and HuggingFace. On the infrastructure side, we also work with platforms like Google Cloud AI and Azure ML.
Does it integrate with our existing business systems?
Yes. We build AI solutions fully integrated with Zoho CRM, RPA tools and the other business systems you use. The goal is not to add yet another tool, but to build a system that works inside your existing flow.
Let's build the core of your business together.
We prepare a concrete proposal and a live demo based on your current system, your goals, and your timeline. No commitment before the contract.
Your details are processed under the KVKK Privacy Notice and we get back to you within 24-48 hours.
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