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AI & Machine Learning

AI Development Company: What to Look for Before You Sign a Contract

Most AI vendors sell demos. Few ship production systems. Here is what to verify before you sign with an AI development company.

Udayra AI Team11 min read

Choosing an AI development company in 2025 means separating demo builders from teams that operate models in production. This checklist is what we recommend enterprise and startup buyers use before signing.

Evaluation before models

Serious AI partners define metrics and evaluation datasets before picking a model. Ask how they measure accuracy, latency, cost per query, and hallucination rate on your data — not generic benchmarks.

Production and MLOps

  • CI/CD for prompts and retrieval configs
  • Observability dashboards per request
  • Rollback strategy for bad deployments
  • Data pipeline ownership documented

Security and compliance

Clarify data residency, PII handling, model provider DPAs, and access control. AI systems fail audits when retrieval exposes documents users should not see.

Questions to ask before signing

  1. Who owns the prompts, embeddings, and fine-tunes?
  2. What happens if OpenAI or Anthropic changes pricing or policy?
  3. Show me a production incident you handled.
  4. How do you hand off to our internal team?
  5. What is explicitly out of scope?

How Udayra approaches AI delivery

Udayra builds AI for our own products (Intrya, Jyotix) and for clients worldwide. We ship RAG, agents, and ML pipelines with evaluation-first delivery. See our AI development services or hire dedicated AI engineers.

Evaluating AI partners?
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From the authors

How Udayra approaches AI Development Company: What to Look for Before You Sign a Contract

What to look for in an AI development company before signing — evaluation harnesses, production MLOps, security, and questions to ask vendors. This article is the public version of conversations we have with founders and engineering leads before a contract. The goal is a decision you can take into a vendor call, not a generic overview of the category. Read it as a checklist: what to ask, what to refuse, and what “done” should look like in production.

Udayra is the team behind the post: senior engineers in India who ship custom software, AI systems, and dedicated teams for clients in the USA, UK, and other markets. We also run our own products, so the advice is constrained by production cost, quality, and ownership. Related Udayra services for this topic: AI & Machine Learning Solutions, Generative AI & LLM Integration, and AI Agent Development. We will not recommend a rewrite if an integration will do, and we will not staff a demo team for a production problem.

If the checklist or process above matches a live project, send the URL with your brief. We will tell you what we would do in the first month, what we would refuse, and whether a project or a dedicated engineer is the better model. If you only needed the article, use it — that is why it is here. Share it with whoever signs the vendor contract; the questions are written for them as much as for engineering.

Related reading lives in the cards below. Related delivery lives on the services and hire pages. Udayra’s job, if you hire us after this post, is to implement the parts we argued for in public and to document the system so your next hire can take over.

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