The Right AI Platform for What You're Building

An AI platform partner helps you choose which AI platform to build on, then builds on it with you. That means comparing the options against your own use case, data and cloud, setting the platform up inside your accounts, connecting it to your systems, and training your team to run it. A good one will also tell you when the platform you already have is the right one. We hold Google Cloud and AWS partnerships, and we don’t resell any model provider or framework vendor, which is why our Platform Fit Assessment can say that plainly.

Claude and Gemini are families of AI models, made by Anthropic and Google. Amazon Bedrock isn’t a model. It’s Amazon’s service for running several models, including Claude, inside your own AWS account. Google’s equivalent is Vertex AI, which runs Gemini. So the choice is usually two decisions at once: which model suits the task, and which cloud you want it to run on. We build on all of them and compare them against your data, your cloud and your use case in our Platform Fit Assessment.

Keep the things that are yours outside the vendor. Prompts, connectors and the evaluation set sit in your own repository, and nothing is built that only runs on one provider. When a model changes or a better one arrives, you re-run the evaluation set on the replacement and see what moved. Some lock-in is fine, such as running on the cloud you already pay for, as long as it’s a decision you made on purpose. Every Platform Fit Assessment ends with a written recommendation and a migration path in case you ever need to move.

Start with three questions: where your data has to live, which cloud you already run, and what each request would cost at real volume. Platforms can look alike in a demo and still differ sharply on those. Then test the shortlist against your own use case rather than a vendor’s example. Our Platform Fit Assessment (2 weeks, $15K to $25K) does this across Claude, Gemini, Amazon Bedrock, LangChain and Databricks and ends with a written recommendation. If the platform you already have turns out to be the right one, that’s the answer.

It depends on the platform and how much you’re building, but a first production feature is typically a few weeks of fixed-price work. Our Claude-Powered Product Launch is 4 weeks at $35K to $60K, our Gemini Feature Launch is 3 to 4 weeks at $25K to $45K, and our Agent Bricks Launch on Databricks is 4 to 6 weeks at $35K to $65K. For a setup already running on AWS, our Bedrock Well-Architected Review (2 weeks, $15K to $25K) checks cost, security and reliability and gives you a prioritised fix list. Choosing first with the Platform Fit Assessment keeps you from paying to build on the wrong one.

If your engineers have already built on one platform and it’s working, you may not need one. A platform vendor’s own services can also be enough when everything you’re building stays inside that one platform. A partner earns its fee when you’re choosing between several platforms, crossing more than one, or moving off one. If you’re unsure, a two-week Platform Fit Assessment can confirm the platform you have is the right one.