Generative AI & LLM Development

We design and ship LLM-based systems that run in production: secure, measurable, and integrated into real business workflows.

RAG · Evaluation · Orchestration · Secure deployment · Integration

Generative AI solutions for real business use

We help companies move beyond demos and prototypes by designing production-grade generative AI systems aligned with business goals, data constraints, and technical reality.

Our work focuses on custom LLM applications, AI agents, and generative workflows that operate reliably at scale and integrate with existing systems.

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How businesses use generative AI

AI agents for operations

Automate repetitive tasks, monitoring, reporting, and decision support across internal systems.

Customer support automation

LLM-powered chat and ticket handling integrated with CRM, knowledge bases, and internal tools.

Sales & marketing augmentation

AI agents that qualify leads, generate content, personalize outreach, and assist sales teams.

Internal knowledge assistants

Private LLMs trained on company data for search, summarization, and decision support.

Document processing & analysis

Extraction, classification, summarization, and compliance checks using generative models.

Our delivery process

1

Discovery & requirements

Business goals, constraints, data sources, and success metrics.

2

Architecture & model strategy

LLM selection, prompt strategy, fine-tuning vs RAG, security design.

3

Development & testing

Model orchestration, agents, evaluation, and reliability testing.

4

Integration & deployment

APIs, internal systems, cloud infrastructure, and monitoring.

5

Iteration & scaling

Performance optimization, cost control, and continuous improvement.

Architecture & technology

We design generative AI systems with an architecture-first approach.

This includes model orchestration, retrieval pipelines, agent frameworks, and integration layers — built for reliability, scalability, and long-term operation.

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Why work with us

Architecture-driven, not demo-driven
Business outcomes over hype
Experience with real production systems
Clear technical communication
Focus on ROI, scalability, and control

We work as technical partners, not vendors.

Let's discuss your generative AI project

Have an idea, prototype, or existing system? We'll review it and suggest a clear technical and business path forward.

Frequently asked questions

How long does a generative AI project take?
From 3–6 weeks for a focused MVP to several months for production systems.
Do you use OpenAI, custom models, or open-source LLMs?
We select models based on requirements, data sensitivity, cost, and performance.
Can you integrate with existing systems?
Yes — CRM, ERP, databases, APIs, and internal tools.
How do you handle data security?
Private deployments, controlled access, and secure architecture by design.
Do you offer ongoing support?
Yes — monitoring, optimization, and scaling support.

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