AI Development

Turn data into decisions with production-grade AI.

From custom LLM-powered agents to recommendation engines and enterprise ML pipelines — we build AI that actually ships, scales, and delivers business value.

Capabilities

AI services, engineered for the real world

We cut through the hype and build AI that solves specific business problems — measurable, reliable, and production-ready.

Custom AI Agents

Autonomous agents that handle support, sales qualification, research, or internal workflows using function-calling and tool use.

RAG Systems

Retrieval-augmented generation pipelines that let LLMs answer accurately from your private knowledge base or documents.

LLM Integrations

Plug GPT-4, Claude, Gemini, or open-source models directly into your product with robust prompt engineering and guardrails.

Recommendation Engines

Personalized product, content, or course recommendations powered by embeddings and vector search at scale.

AI Chatbots & Assistants

Intelligent support, onboarding, and in-app assistants that learn your product, tone, and policies — no generic chatbot feel.

ML Model Training

Custom classification, prediction, and clustering models built on your proprietary data, deployed with MLOps best practices.

Document Intelligence

Extract, classify, and structure data from PDFs, contracts, forms, and emails using OCR + LLM pipelines.

AI Safety & Evaluation

Testing, red-teaming, and guardrail frameworks that keep your AI accurate, safe, and aligned with your brand values.

Our Process

From concept to production in weeks, not quarters

Discovery

Problem framing, data audit, and success metrics. No AI for AI's sake.

Prototype

2-week proof-of-concept to validate approach, cost, and performance.

Build

Production-grade infrastructure with monitoring, evals, and guardrails.

Iterate

Continuous improvement based on real usage data and user feedback.

Our Stack

Tools & frameworks we trust

OpenAI

Anthropic

Gemini

Python

LangChain

LlamaIndex

Pinecone

Weaviate

PyTorch

TensorFlow

AWS Bedrock

Hugging Face

Engagement

Pricing & timelines

Most AI projects fall into one of three buckets. We’ll scope the right fit after an initial call.

AI Quick Win

LLM integration, simple chatbot, or single-feature AI addition.

$8K – $20K

2–4 weeks

Custom AI Product

RAG systems, custom agents, or AI-powered product features with full production infrastructure.

$25K – $80K

6–12 weeks

Enterprise AI

Custom ML model training, large-scale deployments, and ongoing AI platform partnership.

$80K+

12+ weeks

FAQ

Common AI questions

Do we need a lot of data to build useful AI?

Not as much as you’d think. With modern LLMs and RAG techniques, we often build high-value AI features using just your existing documentation, product data, or user content.

How do you handle hallucinations and accuracy?

Every system we build includes evaluation frameworks, source citations, guardrails, and fallback behaviors. We also set up automated testing so accuracy is monitored continuously — not guessed at.

Which LLM provider should we use?

It depends on your use case, cost constraints, and privacy requirements. We often deploy with multiple providers to handle different tasks and keep costs optimized. We’ll advise based on your specific needs.

Can you work with our sensitive data?

Yes. We offer private cloud deployments, on-premise options, and providers with zero-data-retention policies. HIPAA, SOC 2, and GDPR-compliant setups are all supported.

What ongoing costs should we plan for?

Typical production AI features run $200–$5,000/month in infrastructure and API costs, depending on scale. We design with cost efficiency in mind and give you clear projections before building.

Ready to add real AI to your product?

Book a 30-minute call and we’ll sketch out a path — what’s possible, what it costs, and whether AI is even the right move.