Which AI and LLM models do you support?

We build with OpenAI models, Anthropic Claude and open-source Llama architectures. We select the best fit according to latency, cost and privacy requirements, using lightweight models for classification and frontier models for reasoning.

How do you protect enterprise data privacy?

We enforce zero-data retention enterprise terms so your data is never used to train public models. Sensitive customer identifiers are sanitized locally before processing, and we deploy self-hosted models for strict compliance needs.

How do you keep model API expenses under control?

We deploy semantic caching to resolve recurrent queries locally without triggering external API calls. Granular user quotas, rate limiting and budget alerts ensure your monthly operating expenses remain predictable.

Can AI connect to our existing CRM or ERP platform?

Yes. Rather than replacing your operational software, we connect custom AI endpoints directly to your existing databases, CRM and ERP via secure APIs. Your team leverages automated intelligence without leaving familiar software.

What advantages does RAG architecture provide?

RAG ensures models generate answers grounded strictly in your verified internal documentation and records rather than guessing from web data. This minimizes hallucinations and produces factual answers citing exact source references.

Services / Our Services

AI Solutions & LLM Integration

At Candemsoft, we approach AI not as marketing hype, but as an engineering discipline that shortens workflows. Based in Istanbul, our team integrates Large Language Models (LLMs), semantic search and document parsing into your systems. We transfer real-world lessons from our products Orpigo and Candemkey into secure AI architectures.

Target & Use Cases

Who Can Benefit from Our AI Solutions?

We deliver solutions for organizations looking to increase operational efficiency through intelligent systems.

Companies Automating Repetitive Workflows

We automate support tickets, invoice parsing and document summaries to lift operational workload from your team.

Teams Adding LLMs to Existing Software

Without rebuilding your CRM or ERP, we embed natural language processing and smart queries at the API layer.

Organizations with Rich Knowledge Repositories

We turn internal manuals and archives into searchable, conversational assistants using RAG architecture.

Startups Building AI-First Products

We guide startups building AI-native mobile and web apps with architecture, prompt tuning and cloud deployment.

Work Process

How We Deliver AI Projects

We advance through structured milestones, measurable ROI and strict data security protocols.

01
Feasibility & Use Case Scoping
We identify which workflow steps yield genuine time and cost savings with AI to define precise scope.
02
Model Selection & Architecture
We evaluate latency, budget and privacy constraints to select the optimal proprietary or open-source model.
03
Prompt Engineering & RAG Setup
We configure vector databases, connect contextual retrieval pipelines and calibrate model prompts with test datasets.
04
Security Guardrails & System Integration
We implement data sanitization guardrails and connect secure API endpoints directly to your production databases.
05
Deployment & Observability
We roll out to production, monitoring token burn rates, latency and output accuracy via real-time telemetry.

Deliverables

What Deliverables Do You Receive?

We deliver fully documented, production-ready AI components built for stability and scale.

✓

Production-Ready AI APIs

High-availability REST and GraphQL backend services engineered to integrate with your existing software stack.

✓

Vector Database & RAG Pipeline

Vector indexing architecture that parses corporate documents to generate factual, context-aware responses.

✓

Admin Console & Prompt Management

Web-based console allowing your team to update system prompts, review audit logs and verify model output.

✓

Token Quota & Cost Control Layer

Semantic caching and quota throttling layers that keep third-party model inference costs strictly predictable.

Technologies we use

Technologies We Use

We rely on reliable, scalable and modern tools for artificial intelligence architectures.

Python
Node.js
TypeScript
Docker
AWS
C#

Our Architecture Standards & Technical Principles

Practical AI Over Hype: Delivering Measurable Business Value

We treat artificial intelligence as an operational efficiency lever rather than marketing window dressing. Before applying an LLM, we verify whether deterministic software logic or probabilistic inference yields better ROI. A well-designed workflow cuts hours of manual document review down to automated seconds.

Field lessons from our products—low-latency processing in Orpigo and instant text rewriting in Candemkey—directly shape our enterprise implementations, ensuring fast, stable performance under real production workloads.

Turning Enterprise Documents into Intelligent Assistants with RAG

Foundation language models lack knowledge of your proprietary internal policies, product specifications and contracts. To feed this context securely, we establish RAG pipelines that segment and index corporate documents into high-speed vector databases.

When a query arrives, our retrieval engine fetches relevant passages and passes them to the model context. The model synthesizes answers citing verified internal sources, minimizing speculative drift and safeguarding organizational trust.

Data Governance and Token Cost Management

The primary priorities in corporate AI deployments are sensitive data governance and predictable operating expenses. Our middleware layers sanitize customer identifiers and private data locally before any API request leaves your infrastructure.

On the cost side, semantic caching fulfills recurrent queries locally, while smart model routing sends simpler tasks to lightweight models, keeping token consumption efficient without compromising accuracy.

Experience & Track Record

We apply the same engineering rigor to our own in-house products and client systems.

Mobile app and website→

Orpigo

Orpigo is an ORP speed-reading app that keeps words at your focal point to cut eye movement. Upload PDFs and read faster today; download the app now.

Mobile app and website→

Candemkey

Candemkey is a Turkish smart AI keyboard that fixes grammar, drafts professional emails and translates text across all your apps. Try it today.

FAQ

Frequently Asked Questions

Which AI and LLM models do you support?: We build with OpenAI models, Anthropic Claude and open-source Llama architectures. We select the best fit according to latency, cost and privacy requirements, using lightweight models for classification and frontier models for reasoning.
How do you protect enterprise data privacy?: We enforce zero-data retention enterprise terms so your data is never used to train public models. Sensitive customer identifiers are sanitized locally before processing, and we deploy self-hosted models for strict compliance needs.
How do you keep model API expenses under control?: We deploy semantic caching to resolve recurrent queries locally without triggering external API calls. Granular user quotas, rate limiting and budget alerts ensure your monthly operating expenses remain predictable.
Can AI connect to our existing CRM or ERP platform?: Yes. Rather than replacing your operational software, we connect custom AI endpoints directly to your existing databases, CRM and ERP via secure APIs. Your team leverages automated intelligence without leaving familiar software.
What advantages does RAG architecture provide?: RAG ensures models generate answers grounded strictly in your verified internal documentation and records rather than guessing from web data. This minimizes hallucinations and produces factual answers citing exact source references.

Let's discuss your project

Let's evaluate your requirements, architectural needs, and roadmap. Contact our Istanbul-based engineering team today.

Write to us