AI Development
AI That Automates Work, Not Just Generates Text
Global AI spending is projected to surpass $300 billion in 2026. But most companies waste budget on AI features nobody uses. We build AI systems that automate specific workflows, process documents, answer customer questions, and make predictions — using Claude, GPT-4o, and open-source models. Organizations that deploy targeted AI report strong ROI within the first year.
Enterprise AI That Delivers Measurable Results
65% of enterprises increased their AI budgets in 2026, with a median increase of 22% year-over-year. 65% of organizations now use generative AI in at least one business function. The technology has moved past the hype cycle into production deployment.
But there's a gap between buying AI tools and getting value from them. Off-the-shelf solutions handle generic tasks. They can't access your internal systems, understand your business logic, or integrate with the workflows your team actually uses. That's where custom AI development fills the gap.
We build AI solutions that plug directly into your operations: chatbots connected to your CRM and knowledge base, document processors that extract structured data from invoices and contracts, prediction engines that analyze your historical data, and autonomous agents that execute multi-step tasks without human intervention. Every system is built on your data, integrated with your stack, and measured against KPIs you define before development starts.
How We Build AI Systems
Use Case First, Technology Second
We start by identifying the specific workflow to automate, the data available, and the success metrics. Then we select the right model and architecture. Some tasks need Claude's reasoning capabilities. Others work better with fine-tuned open-source models. Some don't need LLMs at all — classical ML solves them faster and cheaper.
Prototype in Weeks, Not Months
Every AI project starts with a working prototype in 2-3 weeks. You test it with real data, validate the approach, and measure preliminary accuracy before committing to full development. This eliminates the risk of building something for months only to discover it doesn't fit the actual workflow.
Production-Grade Architecture
A demo that works on your laptop and a system that handles 10,000 requests per hour are different engineering problems. We build for production: rate limiting, fallback models, error handling, monitoring, cost optimization, and graceful degradation. The average developer saves 3.6 hours per week with AI tools — your system should deliver similar measurable gains.
Data Privacy by Design
Enterprise API plans that don't train on your data. Encryption in transit and at rest. Option for on-premises deployment with open-source models when data never leaves your infrastructure. We architect AI systems for compliance with GDPR, CCPA, and industry-specific regulations from the start.
$301B
Global AI spending 2026
5.8x
Average ROI in 14 months
65%
Enterprises increasing AI budgets
84%
Developers using AI tools
Frequently Asked Questions
How much does custom AI development cost?
AI chatbot integrations start at $8,000-$15,000. Document processing systems range from $15,000-$35,000. Custom AI agents with multi-step reasoning and system integrations cost $20,000-$50,000 or more. Enterprise AI platforms combining multiple capabilities can exceed $75,000. We provide fixed-price quotes after a free scoping session that maps your use case to a detailed technical implementation plan.
Which AI models do you work with?
We work with Anthropic's Claude (Claude Opus, Claude 3 Opus), OpenAI's GPT-4o and GPT-4 Turbo, Google's Gemini, and open-source models like LLaMA 3 and Mistral. Model selection depends on your use case, performance requirements, latency tolerance, data privacy needs, and budget. We frequently combine multiple models within a single system — using smaller, faster models for simple tasks and larger models for complex reasoning.
How long does it take to build an AI solution?
A basic AI chatbot integration takes 4-6 weeks. Document processing systems take 6-10 weeks. Custom AI agents with complex multi-step workflows take 10-16 weeks. Enterprise platforms with multiple AI capabilities take 16-24 weeks. We deliver a working prototype in the first 2-3 weeks so you can validate the approach with real data before committing to full development.
Is my data safe when using AI services?
Stop Experimenting with AI. Start Deploying It.
Tell us the workflow you want to automate. We'll assess the technical feasibility, recommend the right approach, and deliver a working prototype in 2-3 weeks.
Free feasibility assessment · Working prototype in 2-3 weeks · Measurable KPIs from day one