Intelligent Chat Assistants
Custom chat assistants powered by your own documents — for customer support or internal teams.
AI Integration
Artificial Intelligence (AI) and LLM Integrations
Intelligent assistants, RAG architectures, automated content generation and data analysis solutions powered by OpenAI, Anthropic and open-source models.
Through artificial intelligence and large language model (LLM) integrations we add chat assistants, intelligent search, automatic summarization or personalized recommendations to your existing product. With OpenAI GPT, Anthropic Claude and open-source (Llama, Mistral) models, we build the right solution for your use case.
We do more than call an API: with RAG (Retrieval-Augmented Generation) architecture we connect your own data to the model and generate controlled, verifiable answers. Vector databases (Pinecone, Qdrant, Weaviate), embedding strategies and prompt engineering are our specialty.
AI features need to integrate tightly with the rest of the product. Hand in hand with our custom web and backend development team we surface AI output cleanly in the UI, track usage metrics and apply cost optimization.
AI cost optimization is an area Sora Yazılım pays particular attention to in production deployments. OpenAI GPT-4o costs ~$2.5 per 1K input tokens, GPT-4o-mini ~$0.15; as query volume grows, the right model choice can swing monthly costs by 10–20x. We use prompt caching, response streaming, hybrid model usage (simple tasks → small model, complex → large), batch APIs and semantic caching to keep your budget under control. A typical mid-size AI chatbot project costs $200–$800/month.
Self-hosted vs API trade-off is a critical decision for organizations with strict data sovereignty requirements. Open-source models like Llama 3.3 70B, Mistral Large and Qwen 2.5 can run on your own GPU servers so your corporate data never leaves your premises. Sora Yazılım handles vLLM, Ollama, HuggingFace TGI deployment, GPU sizing (NVIDIA L40S, H100, MI300X), tokens/second optimization and ongoing operation. We position HPE Apollo and Dell PowerEdge XE9680 AI servers in these projects.
Data privacy and compliance are the #1 blocker for enterprise AI projects. OpenAI API, Azure OpenAI and Anthropic Claude API contractually guarantee that customer data is not used to train models; Sora Yazılım prepares the data-flow diagram, contracts and GDPR/KVKK disclosure for every project. For sensitive data we standardly deploy automatic PII masking, prompt injection protection, jailbreak detection and content moderation layers.
Service Scope
What we build with AI and LLMs
Concrete, measurable features that add real AI value to your product.
Semantic Search
Intent-based, vector-database-powered intelligent search instead of keyword matching.
RAG and Document Q&A
Trusted answer generation grounded in your internal documents, product catalog or knowledge base.
Automated Content Generation
AI-powered automation of product descriptions, email drafts, blog summaries and reports.
Our Approach
We bring your AI project to life in 5 steps
From a pilot to fully product-scaled AI features.
- 01
Use Case Analysis
We identify the scenarios where AI genuinely adds value and define ethical/security guardrails.
- 02
Model & Architecture Selection
We choose among OpenAI, Anthropic or open-source models based on the right cost/performance balance.
- 03
Prompt Engineering & RAG Setup
System prompts, few-shot examples, vector database and embedding strategy are designed and implemented.
- 04
Evaluation and Testing
Measurable evaluation across accuracy, hallucination rate, latency and cost.
- 05
Production & Monitoring
Continuous tracking of token usage, success rate and user feedback once in production.
Technologies
Proven tools from the modern AI ecosystem
LLM Models
OpenAI GPTAnthropic ClaudeLlamaMistral
Frameworks
LangChainLlamaIndexVercel AI SDK
Vector DB
PineconeQdrantWeaviatepgvector
Self-Hosted
OllamavLLMHuggingFace TGI
Example Scenarios
What kinds of AI projects has Sora Yazılım delivered?
24/7 support assistant
A customer support assistant grounded in company documentation that resolves 80% of cases without involving a human agent.
Smart product recommendation engine
Personalized product recommendations based on user behavior and embedding-driven semantic similarity.
Contract analysis tool
An internal tool that automatically summarizes contracts, flags risky clauses and compares versions.
Municipal citizen chatbot
A RAG-based assistant that answers citizens' questions about municipal services, fee payments and applications in Turkish, 24/7, at 100K+ queries per month.
Medical report summarization tool
An internal tool that summarizes a patient's medical history in seconds, flags key findings, and operates in a GDPR/KVKK-compliant manner — increasing physician productivity by 40%.
Solutions We Pair With This
Which solution brands do we deploy alongside?
Global vendor solutions we position within this service scope.
Productivity and Collaboration
Microsoft 365 (Office 365)
Microsoft 365 — formerly Office 365 — is the cloud productivity suite that unifies enterprise email, files, meetings and AI productivity for the modern workplace.
Learn moreServer HardwareHPE Servers (ProLiant)
HPE ProLiant Gen11 and Gen12 servers — powered by 4th/5th Gen Intel Xeon Scalable and AMD EPYC 9004/9005 processors for data center and branch workloads.
Learn moreServer HardwareDell PowerEdge Servers
Dell PowerEdge servers powered by 4th/5th Gen Intel Xeon Scalable and AMD EPYC 9004/9005 processors for data center, branch, edge and AI workloads.
Learn moreAuthoritative Reference
NIST AI Risk Management Framework
Kurumsal AI risk yönetimi için ABD NIST referans çerçevesi.
NIST AI Risk Management Framework →Related Services
Other services that complement your AI project
Custom Web and Backend Solutions
Enterprise-grade custom web applications, SaaS platforms and high-performance backend APIs that place your digital product on a scalable, secure and sustainable foundation.
Mobile Application Development
Native and cross-platform mobile apps for iOS and Android — built by a team that puts user experience first and reliably ships your App Store and Play Store releases.
Digital Transformation and SEO Consulting
A 360° strategy combining technical SEO, content architecture, GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) to boost discoverability across search engines and AI assistants.
Frequently Asked Questions
Common questions about AI and LLM integrations
Use the form for any question not covered below.
Will my data be used to train OpenAI or Anthropic models?
No. Data sent through the OpenAI API and Anthropic Claude API is not used for model training, as the providers document. For highly sensitive data we also offer self-hosted Llama/Mistral models.
How is the risk of hallucination (wrong answers) managed?
With a RAG architecture the model answers only from the documents you provide. On top of that, guardrail libraries, validation layers and user feedback loops continuously drive the hallucination rate down.
Is the cost predictable?
Yes. We share an estimated monthly cost based on token usage, model choice and embedding strategy. With caching, prompt compression and smaller-model strategies we typically reduce cost by 40–70%.
How does it perform in non-English content?
GPT-4 and Claude 3.5+ models deliver strong performance in major languages, including Turkish. For domain-specific content (legal, medical, finance) we recommend fine-tuning or RAG-based customization.
Do you offer self-hosted model solutions?
Yes. For scenarios where data cannot leave your network — banking, healthcare and public sector — we host Llama 3, Mistral or domain-specific fine-tuned models on your own infrastructure with Ollama, vLLM or HuggingFace TGI.
How do you measure AI feature usage and quality?
We track token usage, latency, success rate, user feedback (thumbs up/down) and A/B test results with Langfuse, Helicone or our own dashboard. Monthly reports are included.
Can you integrate with our existing chatbot platforms?
Yes. We integrate with Intercom, Drift, Zendesk, the WhatsApp Business API, Telegram and custom platforms. We layer AI on top of your existing workflow without disrupting it.
Is fine-tuning required?
In most cases no. Most needs are met with a RAG architecture and well-crafted system prompts. We only recommend fine-tuning when very specific linguistic style or domain-specific terminology demands it.
How long does an AI project typically take?
A simple chatbot prototype takes 2 weeks, a RAG-based intelligent assistant 4–8 weeks, and a complex multi-agent system 3–6 months. We strongly recommend starting with a quick POC.
Can you build multi-modal (image + text) AI solutions?
Yes. We use the vision capabilities of GPT-4o, Claude 3.5 Sonnet and Gemini to deliver multi-modal scenarios such as invoice OCR, product image recognition, screen content analysis and OCR + reasoning workflows.
Request Form
Let's talk about your AI project
Share your use case and get an expert recommendation within 24 hours.
24-hour response
We work Monday–Friday, 09:00–18:00 (TRT).
Your data is safe
GDPR/KVKK compliant — never shared with third parties.
Free discovery call
No commitment required; a proposal follows.
Ready to add real AI value to your product?
In a free discovery call we share an ROI estimate and a technology recommendation tailored to your scenario.