AI Development Company That Ships Production Systems — Not Demos.

End-to-end AI development across four areas: custom AI and LLM application development (RAG, generative features, fine-tuning, NLP and document pipelines); AI agents and automation for systems that act, not just answer; AI platform and orchestration for multi-model routing, context injection, and cost control; and AI integration into existing products and data. We’re model-agnostic across OpenAI, Anthropic, Google Gemini, and open-source models, and we take systems all the way to production — with evals, guardrails, monitoring, and compliance built in.

We treat productionizing as its own engineering discipline. Starting from your PoC, we harden the data pipeline, select the right model for cost and latency, build the orchestration and integration into your real systems, and add the two things prototypes almost always lack: an evaluation set that measures accuracy objectively, and guardrails that catch hallucinations and unsafe actions before users see them. Then we wire in monitoring, drift detection, automated retraining, and cost controls. The result is a versioned, monitored, scalable service — not a notebook.

All of them — we’re deliberately model-agnostic. We match the model to the job: a frontier LLM (GPT, Claude, Gemini) where reasoning matters, a smaller or open-source model (Llama, Mistral) where cost and latency dominate, and classical ML where the task is narrow. For clients running more than one, we build an orchestration layer that routes each request to the right model with fallback and cost-based routing, so you’re never locked into a single vendor or paying frontier prices for easy tasks.

It depends on scope and engagement model. Application builds typically run as a dedicated team or a fixed-price engagement scoped to a defined feature set; exploratory work usually starts as a Time & Materials PoC, because the real effort emerges once we see your data. The main cost drivers are data quality and volume, model choice, integration complexity with your existing systems, compliance requirements, and target scale. We give you a firm, itemized estimate after a technical scoping call.

Yes — this is one of our core strengths. Much of our AI work is integration: connecting models to your databases, document stores, ERPs, EHRs, and internal APIs so the AI can read and act on your real data. We built the orchestration between Python ML services and Odoo ERP for Eska’s lending platform, and EHR integration with Epic and Cerner for Martti. Our dedicated system integration practice handles the connective tissue, and we build AI business tools directly into the workflows your team already uses.

With evaluation and grounding, not hope. Before production we build an eval set and ground-truth benchmarks so accuracy is measured objectively. In the system itself we ground outputs in your data via retrieval (RAG), validate inputs and filter outputs, and add human-in-the-loop gates for high-stakes actions so a model never takes an irreversible step alone. In production, monitoring tracks quality and drift, and automated retraining keeps the system accurate as your data changes.

Yes. We have HIPAA, GDPR, and KBV delivery experience, and we architect compliance in from the start — encryption, data residency, access controls, and auditability designed in rather than retrofitted. We built HIPAA- and SOC 2-compliant AI-assisted interpretation for Martti across 4,000+ hospitals, and an auditable, explainable risk-scoring model for Eska in leasing. For regulated healthcare AI specifically, see our clinical AI practice.

A dedicated Tech Lead with direct CTO access, a shared Slack channel, board access (Jira/Linear), and sprint demos every two weeks. Our team is based in Ukraine (GMT+2) with overlap across EU and US business hours, plus European offices in Valencia and London.