AI & Machine Learning Consulting for Production Systems

Most organizations do not need another AI demo. They need systems that answer questions accurately, automate real workflows, and stay within budget when traffic spikes. Froxfire helps teams move from experimentation to production-grade machine learning — with architecture your engineers can own long after launch.

What we deliver

Our AI consulting practice covers the full stack: data preparation, model selection, orchestration, evaluation, and the operational layer that keeps everything running reliably. We are model-agnostic by design, so you are never locked to a single vendor when better options emerge.

• Retrieval-augmented generation (RAG) — Grounded answers from your documents, databases, and APIs with chunking strategies, embedding pipelines, and relevance tuning tuned to your domain.
• AI agents — Tool-using agents that plan, act, and recover from failure with guardrails, human-in-the-loop checkpoints, and audit trails.
• Custom models — Fine-tuning, distillation, and evaluation frameworks built around your data — not generic benchmarks.
• Model gateway — A single API across OpenAI, Anthropic, open-weight models, and internal endpoints with caching, rate limiting, and spend controls.

Use cases we solve

Teams come to us when off-the-shelf chatbots fall short. Common engagements include internal knowledge assistants for regulated industries, document extraction and classification at scale, customer support copilots with escalation logic, and geospatial AI pipelines that combine satellite imagery with structured operational data.

We also help organizations consolidate fragmented AI experiments into a coherent platform — shared evaluation harnesses, prompt versioning, and deployment patterns that reduce duplicate engineering across business units.

Built for observability and cost control

Production AI fails silently without the right instrumentation. Every system we build includes tracing for prompts and tool calls, latency and token metrics, quality evaluation loops, and alerting when drift or error rates climb. Cost governance is built in from day one — not bolted on after the first surprise invoice.

Security and compliance are defaults: least-privilege access to data sources, encryption in transit and at rest, and clear data retention policies aligned with your regulatory environment.

Whether you are launching a first production LLM feature or scaling an existing AI platform, we help you move fast without sacrificing reliability or governance.

Why Froxfire

We are a senior engineering studio, not a slide-deck consultancy. The architects who scope your AI initiative are the same engineers who write the pipelines, tune the retrieval, and stand up the gateway. That continuity matters when timelines are tight and stakes are high.

Explore our full services overview, or contact us to discuss your AI roadmap. We typically respond within one business day.