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Veracy Advisory Platform

AI Tools for Building and Deploying AI Features

Building AI into a product — not just using AI tools — requires a different set of decisions: which model to use, how to manage latency and cost, how to handle failures, and how to evaluate output quality at scale. The tools in this space are maturing fast.

How teams typically do this

  1. Step 1 — Design the feature

    Claude

    Write system prompts and define AI behaviour

  2. Step 2 — Call the API

    Anthropic Claude

    Integrate Claude or GPT into your product

  3. Step 3 — Build the interface

    Cursor

    Code the user-facing AI feature with AI assistance

  4. Step 4 — Monitor quality

    Langsmith

    Trace, evaluate, and debug AI outputs in production

Best tools to build ai-powered products

1
Claude Listed

The leading API for building AI applications that require strong reasoning, careful instruction following, and safe outputs. Best in class for tasks that need nuance, long context, and reliability.

$ Small business Mid-market Enterprise
2
ChatGPT Listed

The most widely integrated AI API with the largest ecosystem of tools, libraries, and documentation. GPT-4o's speed and multimodal capabilities make it the default choice for most product teams.

$ Small business Mid-market Enterprise
3

The most popular framework for building LLM-powered applications. Handles retrieval-augmented generation, chaining, agents, and memory so you don't have to build everything from scratch.

$ Small business Mid-market Enterprise

Browse all tools for this workflow: API & Backend , Foundation Models

Prompts to get started

Related workflows