--- title: "APIs AI Tools" type: "Category Hub" url: "https://aidemos.com/categories/developer-tools/apis" description: "Evidence-backed AI tools, rankings, comparisons and guides in APIs." totalItems: 20 --- # APIs Part of [Developer Tools & APIs](https://aidemos.com/categories/developer-tools) Explore the APIs category for structured AI extraction, web data collection, and vision intelligence you can plug directly into agent workflows. Tools like **LlamaParse**, **Hireability**, **Airparser**, and **Affinda** turn messy resumes into clean structured data, while **Firecrawl** and **Oxylabs Web Scraper API** extract web content at scale for LLM-ready pipelines. You’ll also find APIs like **Google Cloud Vision API** and **Amazon Rekognition API** for image analysis, plus **Jina AI Reader API** for fast content extraction built for AI systems. ## Rankings - [Best AI Tools for Memory for AI Agents](https://aidemos.com/best/ai-agent-memory-tools) — We tested five memory tools with the same multi-session prompts to see which ones can remember user style, client history, project direction, and delete/forget requests without leaking stale context. - [Best AI Tools to Scrape Web Pages Into Clean Markdown or Structured Data](https://aidemos.com/best/ai-web-scraping-tools) — We tested four AI web-scraping tools on three live targets—a cluttered recipe blog, a JS-heavy Nike product page, and a protected Glassdoor jobs page—to see which ones return usable Markdown or structured data with zero manual selectors. - [Best AI APIs to Convert Complex PDFs to Clean Markdown](https://aidemos.com/best/pdf-to-markdown-apis) — We tested hosted PDF-to-markdown APIs on the same three hard documents: a long hybrid annual report, a table-heavy financial report, and an image-only scanned research paper. The goal was usable markdown with OCR, tables, charts, and reading order preserved well enough for downstream RAG, search, and reuse. - [Best AI Tools for Parsing Resumes via API (2026)](https://aidemos.com/best/resume-parsing-api) — This ranking evaluates AI resume parsing APIs based on their ability to convert resume PDFs into structured, machine-readable data. Using the same three resume inputs across all tools—a clean single-column resume, a multi-column sidebar resume, and a messy real-world resume—we tested extraction accuracy, layout handling, JSON consistency, and automation readiness. The analysis highlights which APIs are best suited for ATS platforms, recruitment software, HR-tech products, and large-scale hiring workflows. ## Use Cases - [Query Live Databases Using Plain English with AI](https://aidemos.com/use-cases/query-live-databases) — This use case shows how business users can query a live database using plain English instead of writing SQL. We tested five AI database tools on the same ecommerce database and found AskYourDatabase to be the best practical workflow because it showed generated SQL, returned readable business answers, handled follow-ups well, and surfaced operational risks like pending-but-paid orders. The page also covers real outputs, limitations, and when users should still review the SQL before acting on results. ## Tools - [Supermemory](https://aidemos.com/tools/supermemory) — Hosted agent memory with strong capture and scoping, but mixed retrieval and weak forget behavior. - [Airparser](https://aidemos.com/tools/airparser) — Structured resume parsing across clean, multi-column, and messy PDFs, with fast JSON output and a few field-quality caveats. - [Firecrawl](https://aidemos.com/tools/firecrawl) — Reliable on JavaScript-heavy and bot-protected pages, but its markdown output usually needs a cleanup step. - [Jina AI Reader](https://aidemos.com/tools/jina-ai-reader) — Turns public URLs into LLM-ready text, with the strongest tested results on static pages and weaker results on JS-heavy or protected sites. - [Spider](https://aidemos.com/tools/spider) — Fast static-page scraping, but weak cleanup and poor reliability on dynamic or protected sites. - [Upstage AI](https://aidemos.com/tools/upstage-ai) — Solid on native financial tables, but unreliable for multi-column and scanned-document structure in markdown conversion. - [Nutrient.io](https://aidemos.com/tools/nutrient-io) — A developer-first PDF-to-markdown API that handles straightforward OCR and hierarchy well, but loses fidelity on complex tables, charts, and handwritten visual content. - [Landing AI](https://aidemos.com/tools/landing-ai) — A capable PDF-to-markdown API for complex financial and scanned PDFs, with strong table and chart extraction but inconsistent heading semantics. - [Mistral AI](https://aidemos.com/tools/mistral-ai) — A strong hosted PDF-to-markdown API for mixed and scanned documents, with solid OCR, table recovery, and asset export but uneven structural fidelity. - [AskYourDatabase](https://aidemos.com/tools/askyourdatabase) — AskYourDatabase Review: NL2SQL AI Database Chatbot Tested (2026) - [Hireability](https://aidemos.com/tools/hireability) — HireAbility Review: Resume Parsing API for Structured Data Extraction Tested (2026) - [LlamaParse](https://aidemos.com/tools/llamaparse) — LlamaParse Review: AI Resume Parser & Schema Extraction Tested (2026) - [Hrflow](https://aidemos.com/tools/hrflow) — HrFlow Review: AI Resume Parsing API Tested (2026) - [Extracta Labs](https://aidemos.com/tools/extracta-labs) — Extracta.ai Review: AI Resume Parser & Custom Field Extraction Tested (2026) - [Affinda](https://aidemos.com/tools/affinda) — Affinda Review: AI Resume Parser Tested Across Resume Formats (2026)