162 AI tools reviewed with real pricing, quickstart code, and honest gotchas
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If your paycheck depends on AWS, this is a no-brainer; for everyone else, it's a tough sell. The 'Code Transformation' agent that auto-upgrades old Java apps is a killer feature that justifies the subscription alone for enterprise teams. However, for day-to-day general coding, it feels like 'Corporate Copilot'—powerful and secure, but slightly less fluid than GitHub's offering.
You.com has successfully pivoted from a consumer search engine to a vital infrastructure provider for AI agents. If you are building a RAG pipeline, this is one of the best 'out-of-the-box' solutions because the data returned is already cleaned, cited, and chunked for your LLM context window—saving you the headache of building a custom scraper. However, if you just need cheap, high-volume rank tracking or raw HTML parsing, stick to traditional SERP APIs like Serper or Bing.
Tavily is the 'lazy developer's' best friend for RAG—and that's a compliment. If you are building an AI agent and don't want to maintain a headless browser farm or write regex to parse HTML, pay the premium for Tavily. It delivers LLM-ready text directly. However, if you are doing high-volume, simple keyword tracking, the $8/1k query price tag (vs Serper's ~$1) will eat your margin alive. Use it for complex agentic research, not rank tracking.
Serper has quickly become the default search tool for AI engineers using LangChain because it's fast, returns clean JSON, and—crucially—doesn't force you into a monthly subscription. Unlike competitors that expire your credits every 30 days, Serper's pre-paid credits last for a year, making it the perfect choice for intermittent RAG workloads or side projects. Use this if you need speed and Google data; avoid it if you require multi-engine support (Bing/Yandex) or enterprise-grade SLAs.
SerpApi is the 'reliable old guard' of search scraping—it's expensive and can be slow, but it returns the most complete structured data you'll find. If you need deep access to Google Shopping, Maps, or Knowledge Graphs, it is worth the premium. However, for high-volume, simple text retrieval for RAG, it is overkill; cheaper and faster alternatives like Serper or Tavily are better suited.
Exa is arguably the best 'search tool' for RAG pipelines because it doesn't just give you links—it gives you the clean content your LLM actually needs. Its neural search capabilities allow for fuzzy, concept-based queries that traditional keyword APIs fail at. However, at $5/1k requests, it is a premium tool; if you just need a list of URLs, stick to Tavily or Serper, but if you need deep context and content extraction in one go, Exa is worth the cost.
Brave is the only serious game in town if you want a search API that doesn't just wrap Google or Bing. It's cleaner, faster, and safer for RAG because it returns structured 'smart chunks' rather than messy HTML, and you won't get rug-pulled by a scraper API getting banned. However, its index is smaller than Google's, so if you need ultra-niche long-tail results, you might still need a backup. Use this if you're building serious AI agents; skip it if you just want the cheapest possible way to scrape Google.
Unify AI is a clever 'neural router' for developers who want to automate the decision of which model to call. Instead of hard-coding 'GPT-4', you let Unify pick the best provider based on your live latency and cost constraints. It's excellent for optimizing spend without sacrificing quality, but the proprietary nature of the router and the additional SaaS subscription layer might be overkill for simple apps that just need a reliable pipe.
Portkey is essentially 'Datadog for LLMs' wrapped in a routing layer. It is the go-to tool for engineering teams that need to debug complex agentic workflows and ensure 99.99% uptime via aggressive fallback strategies. However, if you are building a simple wrapper with a single provider and zero budget for observability, the log-based pricing and slight latency overhead make it overkill.
Martian is a 'smart' router that tries to outsmart the LLM market for you. Instead of you hard-coding 'GPT-4', it analyzes your prompt and routes it to the cheapest model that can handle it (e.g., Flash or Haiku). It's excellent for enterprises burning cash on generic queries, but the $20/mo starting price and opaque routing logic make it less attractive for hobbyists compared to OpenRouter. Use it if you need 'Airlock' compliance or have massive volume where a 20% cost cut pays for the subscription.
LiteLLM is the 'Swiss Army Knife' of AI gateways—it connects to absolutely everything and is the default choice for Python shops wanting to avoid vendor lock-in. It's fantastic for startups and internal tools where flexibility beats raw speed. However, serious infrastructure teams might find the Python-based latency and memory overhead prohibitive at massive scale, where Rust-based competitors like TensorZero or Bifrost perform better.
Keywords AI is a polished 'DevOps for LLMs' platform that shines for startups needing an all-in-one solution for routing, logging, and prompting without managing infrastructure. Its $9/seat Pro plan is aggressively priced for indie hackers. However, infrastructure purists should beware: it is a closed-source SaaS that adds a documented 50-150ms latency overhead to every request. Use it if you want a beautiful UI and zero maintenance; avoid it if you need bare-metal performance or self-hosted sovereignty.
