[{"data":1,"prerenderedAt":112},["ShallowReactive",2],{"blog-\u002Fblog\u002Fhow-to-evaluate-an-ai-product-development-company":3},{"id":4,"title":5,"author":6,"body":7,"date":90,"description":91,"extension":92,"faqs":93,"meta":103,"navigation":104,"path":105,"seo":106,"stem":107,"tags":108,"__hash__":111},"blog\u002Fblog\u002Fhow-to-evaluate-an-ai-product-development-company.md","How to Evaluate an AI Product Development Company Before You Hire One","Attiate",{"type":8,"value":9,"toc":80},"minimark",[10,14,17,22,30,33,37,40,43,47,50,53,57,60,63,67,70,74,77],[11,12,13],"p",{},"Hiring an AI product development company is different from hiring a general software\nvendor. The engineering fundamentals still matter — clean code, tests, sane\narchitecture — but AI adds a layer most procurement checklists don't cover: how do you\nknow the feature will actually work once real users start relying on it?",[11,15,16],{},"Here's what to actually check before signing anything.",[18,19,21],"h2",{"id":20},"_1-ask-how-theyll-evaluate-the-ai-before-launch-not-after","1. Ask how they'll evaluate the AI before launch, not after",[11,23,24,25,29],{},"Any AI feature — a chatbot, a document extractor, an agent — will be wrong sometimes.\nThe question isn't whether it fails, it's whether the team has a way to ",[26,27,28],"em",{},"measure"," how\noften, on what kinds of inputs, before your users become the test set.",[11,31,32],{},"A vendor with real AI engineering experience will talk specifics: a golden set of test\ncases, an evaluation harness that scores outputs against it, and a threshold for what\n\"good enough to ship\" means. A vendor without this will talk in generalities —\n\"we'll test it thoroughly\" — with nothing you could actually inspect.",[18,34,36],{"id":35},"_2-check-whether-theyre-locked-into-one-ai-provider","2. Check whether they're locked into one AI provider",[11,38,39],{},"Some vendors build exclusively on a single model provider because that's the API they\nknow, not because it's the right fit for your problem. Model capabilities, pricing, and\nrate limits all shift quickly, and a system hard-wired to one provider is expensive to\nmigrate later.",[11,41,42],{},"Ask directly: \"If we needed to switch models in six months, what would that cost us?\"\nA team that designed for this from the start will have a clear answer. A team that\ndidn't will describe a rewrite.",[18,44,46],{"id":45},"_3-ask-what-happens-when-the-ai-is-uncertain-or-wrong","3. Ask what happens when the AI is uncertain or wrong",[11,48,49],{},"Guardrails matter as much as the happy path. Does the system have a way to recognise\nwhen it's operating outside its confidence zone — and either decline, flag for a human,\nor fall back safely — or does it just produce its best guess regardless?",[11,51,52],{},"This is especially important for anything customer-facing or judgment-sensitive\n(support, legal, financial, medical-adjacent use cases). A vendor who hasn't thought\nabout this hasn't shipped an AI feature to real users before.",[18,54,56],{"id":55},"_4-ask-who-owns-the-code-the-prompts-and-the-model-configuration-afterward","4. Ask who owns the code, the prompts, and the model configuration afterward",[11,58,59],{},"Some vendors deliver a working demo but retain effective control — proprietary\norchestration layers, prompts you can't see, infrastructure only they can operate.\nThat's a dependency, not a delivered product.",[11,61,62],{},"Clarify ownership explicitly before the engagement starts: source code, prompts,\nevaluation datasets, and infrastructure-as-code should all transfer to you, documented\nwell enough that a different team could pick it up.",[18,64,66],{"id":65},"_5-look-for-a-real-timeline-with-a-validation-checkpoint-not-just-a-launch-date","5. Look for a real timeline with a validation checkpoint, not just a launch date",[11,68,69],{},"A credible AI product engagement usually has a checkpoint early on — a working\nprototype validating the riskiest assumption — before the full production build. If a\nvendor proposes a single long timeline with nothing to look at until the end, there's no\nway to catch a wrong assumption before most of the budget is spent.",[18,71,73],{"id":72},"the-short-version","The short version",[11,75,76],{},"Ask for specifics on evaluation, model flexibility, failure handling, and ownership.\nVague, confident answers to all four are a worse sign than a vendor who says \"here's\nexactly how we'd approach that\" and shows you the mechanism, not just the promise.",[11,78,79],{},"If you're evaluating vendors for an AI product build in Chennai or anywhere else, these\nfour questions will tell you more in twenty minutes than a portfolio deck will.",{"title":81,"searchDepth":82,"depth":82,"links":83},"",2,[84,85,86,87,88,89],{"id":20,"depth":82,"text":21},{"id":35,"depth":82,"text":36},{"id":45,"depth":82,"text":46},{"id":55,"depth":82,"text":56},{"id":65,"depth":82,"text":66},{"id":72,"depth":82,"text":73},"2026-07-17","A practical checklist for vetting an AI product development vendor — the questions that separate a real engineering team from a prompt-wrapper shop.","md",[94,97,100],{"question":95,"answer":96},"What is the biggest red flag when evaluating an AI development vendor?","A vendor that can't explain how they'll evaluate the AI feature's accuracy before launch. If the only plan is \"we'll integrate the API and see how it goes,\" there's no way to know whether the feature actually works before your users find out for you.",{"question":98,"answer":99},"Should an AI vendor commit to a specific model upfront?","Be cautious of a vendor that locks you into one model provider before understanding your accuracy, latency, cost, and data-privacy requirements. A model-agnostic approach — choosing the model based on your constraints, and architecting so you can switch later — is usually the more durable choice.",{"question":101,"answer":102},"How much technical detail should a vendor share before you sign anything?","Enough that you could explain the architecture back to someone else. If a proposal is all outcomes and no explanation of how guardrails, evaluation, and monitoring will actually work, that's a sign the detail doesn't exist yet either.",{},true,"\u002Fblog\u002Fhow-to-evaluate-an-ai-product-development-company",{"title":5,"description":91},"blog\u002Fhow-to-evaluate-an-ai-product-development-company",[109,110],"AI Product Development","Hiring a Vendor","DY7iBH4arHYMNYkwC1AP8XlPbRPJscsY9fsR_-Aqcnk",1784471550505]