AI Development Services

We build production AI on your data:

• Custom and fine-tuned models

• LLM applications

• RAG and knowledge systems

• Small language models

• Multimodal AI

Our team also handles deployment, evaluation, and monitoring to ensure they run reliably. We start every engagement by helping you decide whether you even need a custom model or whether an API or a smaller, fine-tuned model is the smarter call.

Often an API is enough; most AI use cases are well served by a frontier model with good prompting and RAG. You genuinely need a custom or fine-tuned model when your data is too sensitive to send to a third party, when you need domain accuracy a general model can't hit, when the model itself is your competitive edge, or when usage is high enough that owning a smaller model is cheaper than paying per API call. We'll tell you which situation you're in, including when the answer is "you don't need us to build a model."

RAG grounds an existing model in your data at query time, best when the gap is knowledge. Fine-tuning adapts a model's behavior/style/accuracy to your examples, especially when the gap is in how it responds.

Building or heavily customizing a model (often a smaller open-weight one) is for when you need ownership, privacy, or domain performance. Most real projects use RAG first, fine-tuning second, and a fully custom model only when it earns its cost.

Less than most people think for fine-tuning: often, a few hundred to a few thousand high-quality, well-labeled examples can meaningfully shift a model on a narrow task. Data quality matters far more than volume. Part of our assessment is telling you whether your data is ready, and building the curation and labeling pipeline if it isn't.

This page covers custom AI models and LLM/GenAI applications.

Classic machine learning (predictive analytics, deep learning, computer vision, and NLP models built from your data) is our ML Development service.

Building a whole new AI product is AI Product Development, and adding AI into your existing systems is AI Integration.

Many projects touch more than one; we'll point you to the right mix.

Three layers:

• RAG grounds answers in your data;

• Evaluation suites measure accuracy against real benchmarks, so quality is a tracked number;

• Output validators plus confidence thresholds escalate low-confidence cases to a human.

We agree on accuracy targets up front and hold the model to them.

We build model-agnostic, behind a provider abstraction, so you can move between OpenAI, Anthropic, Google, Llama, or Mistral with a config change. For maximum independence, we can build on open-weight models you host yourself.

Yes, completely. You own the source code, the trained/fine-tuned model and its weights, the data pipeline, and all IP, with full rights transferred to you. Open-weight or custom models run in your own environment.

Per industry averages, fine-tuning or a focused custom-model project typically runs from around $30,000–$150,000, while training a large model from scratch runs into the hundreds of thousands or millions, which is exactly why we steer most clients toward fine-tuning, SLMs, or RAG instead. Custom work doesn't fit a fixed price list, so we scope your project and give a tailored estimate; our scope generator can give you a quick ballpark in the meantime.

An API-plus-RAG solution can reach a working proof of concept in about a week; a fine-tuned model typically takes a few weeks; a fully custom model with data pipelines and evaluation runs longer. The first step is always a Scope & Design Document that turns your use case into a phased plan.

We build real models (fine-tuning, RAG, evaluation, multi-model routing) rather than rebadging prompt engineering as "custom AI"; we measure accuracy instead of asserting it; and we'll tell you when you don't need us to build a model. Ask us the hard technical questions (architecture, data handling, how we evaluate) and judge from the answers.

Yes. Models drift as the world and your data change, so we run monitoring, drift detection, evaluation, and retraining on an ongoing basis. 80% of our clients stay with us 7+ years.