AI engineered for production, not demos.

Building an impressive AI demo is easy. Operating AI reliably under real traffic, real costs, and real scrutiny is an engineering discipline, and it is one we practice daily in our own products. Ashton Group designs, builds, and operates LLM-powered systems with the same rigor we bring to any production service: observability, failover, cost governance, and honest evaluation.

We build the unglamorous layers that make AI dependable. A centralized gateway that routes every model call with provider failover, caching, retries, and per-feature cost controls. Orchestration frameworks that let agents use tools safely and remember context across sessions. Retrieval pipelines that ground answers in your actual knowledge instead of the model's imagination.

What we deliver

• LLM orchestration and multi-agent workflows built on LangGraph and FastAPI, with tool use, persistent conversation memory, and concurrency-safe execution
• Centralized AI gateways (LiteLLM and similar) providing intelligent provider failover across Anthropic, OpenAI, and others, plus caching, retries, rate limiting, and per-feature cost attribution
• Retrieval-augmented generation done right: embedding strategy, vector search, and knowledge bases built from your documents, runbooks, and wikis
• AI observability and evaluation with tools like Langfuse: tracing, quality scoring, regression detection, and cost tracking per session and feature
• Applied machine learning with scikit-learn and TensorFlow: predictive analytics, forecasting, and automated content analysis over historical and longitudinal data
• AI readiness assessment: where language models genuinely help your business, where they don't, and what your data needs before any of it works

Proven in production

We operate a centralized AI gateway routing all LLM traffic across our own product fleet, and we have engineered agentic platforms for enterprise environments, including an AI-powered incident-engineering system that vectorizes runbooks, support documentation, and institutional knowledge to accelerate production root-cause analysis. Multi-agent orchestration with more than twenty internal tools, running concurrency-safe in production, is work we have already shipped.

Technologies & practices