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Many SMBs and Startups are partnering with Innovative Solutions to leverage their expertise in generative AI. Innovative Tailwinds enables businesses to develop applications using techniques like large language models, computer vision, and predictive analytics to automate processes and create new value for customers.
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AI is moving from experimentation into execution, and forward deployed engineering gives teams a faster, more focused way to turn opportunity into working capability. By putting Forward Deployed Engineers closer to the business, the data, and the users, companies can move beyond planning and start compounding real AI value.
Direct API access helped companies move fast on AI, but speed has a way of becoming infrastructure. This post looks at why more AWS-centered organizations are moving Anthropic, OpenAI, and other models into Amazon Bedrock, and what to evaluate before making the shift.
In our podcast AI Unplugged, Episode 15, ROI, Tokenomics & the AI Bubble, we talk about how the AI conversation is shifting from experimentation to accountability. Customers are no longer only asking what AI can do. They’re asking what changed, what it cost, and whether the result can be measured.
We also explore the operational reality most teams are starting to face: AI usage does not automatically equal AI value. Token consumption, generated output, and faster individual tasks only matter if they improve the workflow, reduce friction, increase consistency, or create measurable business impact.
