An AI engineering consulting firm that ships production systems.
InTheCloud is a senior AI engineering consulting company. We design, build, and operate the production AI systems that retailers, banks, and health systems rely on — agentic workflows, retrieval-augmented generation, evaluation harnesses, MLOps, and the platform engineering that makes AI dependable inside the enterprise.
What our AI engineering teams build
Production AI services
Inference services, retrieval pipelines, and agentic workflows engineered with the same rigor as the rest of your platform.
Evaluation & guardrails
Evaluation harnesses, regression suites, and safety guardrails so quality is measurable — not anecdotal.
AI platform engineering
Shared model gateways, prompt and tool registries, vector stores, and cost controls so AI scales across product teams.
MLOps & observability
Deployment, versioning, telemetry, and lifecycle management for models, prompts, retrievers, and agents.
Related capabilities
- — Enterprise AI implementation: end-to-end programs from discovery to production.
- — Agentic AI: multi-step agents integrated with enterprise systems.
- — All capabilities: software engineering, cloud modernization, and cloud security.
- — Case studies: selected AI engineering work in production.
Frequently asked questions
What does an AI engineering consulting company actually do?
An AI engineering consulting firm pairs senior software engineers with applied AI practitioners to ship production AI systems. The work spans data pipelines, retrieval, model integration, evaluation, observability, security, and the platform engineering that lets AI run reliably in real enterprise environments.
How is AI engineering different from AI strategy consulting?
Strategy consulting produces recommendations. AI engineering consulting ships software. InTheCloud's engagements end with a working, observable, and supportable system in production — not a deck.
Which AI models and clouds do you build on?
We are model- and cloud-agnostic. We deploy Anthropic Claude, OpenAI GPT, Google Gemini, and open-weight models on AWS, Azure, and Google Cloud. Choices are made per workload — based on latency, cost, evaluation results, and data residency — not vendor preference.
Do you embed with our existing engineering team?
Yes. Most engagements run as integrated pods that work alongside your engineers, transfer knowledge, and leave behind documentation, runbooks, and trained in-house teams. Capability transfer is part of every project.
Ready to get back to building?
Tell us about the engagement. We typically respond within one business day with a named builder who can talk substance — not a generic sales pitch.
Prefer email? info@inthe.cloud