End-to-end AI products, engineered in house.
Stokhos Labs ships production AI, ML, and LLM software from first discovery through launch. Our in-house team brings model engineering, full-stack web development, and interactive product craft into one build motion.
One team for the model, the product, and the launch path.
We combine AI architecture, application engineering, and interactive design inside one delivery team, so the work stays coherent from prototype to production.
RAG systems, agent workflows, assistants, internal copilots, and model-powered product features designed around real user tasks.
Custom models, data pipelines, evaluation loops, and MLOps foundations built for reliable production behavior.
Dashboards, SaaS products, APIs, authentication, data views, and admin tools built around the AI system they serve.
Interactive applications, workflow tools, training environments, and real-time experiences where AI needs to feel usable and alive.
From a model idea to a product people use.
The same team designs the model, the application around it, and the way people interact with it. A few of the things we build:
Domain assistants and in-product copilots that take real actions, grounded in your data and tuned to the workflows your users actually run.
RAG pipelines over your documents and databases, with retrieval quality, citations, and evaluation built in, not bolted on.
Multi-step agent workflows that plan, call tools, and complete tasks, with the guardrails and observability to run them in production.
Task-specific models, fine-tuning, and evaluation harnesses when an off-the-shelf model is not accurate, fast, or cheap enough.
The ingestion, transformation, and serving layers that turn raw data into something a model and an application can actually use.
Simulations, training environments, and real-time application experiences where AI has to feel responsive and alive, not just correct.
Fast prototypes, disciplined builds, production handoff.
Map the product goal, user workflow, data reality, risk areas, and the smallest useful AI surface worth testing.
Build a thin, working version with real interactions, representative data, and evaluation criteria before expanding scope.
Harden the model path, web application, integrations, observability, and deployment patterns into one production system.
Launch, monitor, iterate, and prepare the system for new users, new data, and the next layer of product capability.
Pick the depth that fits the problem.
Whether you need a fast proof of concept or a full product team, the work is run by the same in-house engineers from day one.
A focused build to validate an AI idea fast: a working prototype on real data with clear evaluation, in weeks rather than quarters.
Full product delivery from discovery to production: model, application, deployment, and iteration, owned by one accountable team.
An ongoing partnership where our engineers work as an extension of yours, shipping and scaling AI alongside your roadmap.
Less handoff. More product momentum.
AI products break when model work, application work, and user experience work happen in separate lanes. We keep those disciplines together, which lets the same team reason about retrieval quality, model behavior, interface constraints, deployment, and iteration cadence.
The result is a tighter path from idea to usable software: fewer translation layers, faster technical decisions, and a product team that can adjust the whole system when the data or user workflow changes.