AI · alternatives · 2026
24 alternatives to No-code AI-powered API endpoints
Backengine is a tool that evolved from an experiment at my startup for which we wanted to pass structured data to an LLM completion API and receive structured data back. We thought we'd release it as a standalone tool for others who might also find it useful. Backengine lets you create hosted API endpoints for which the endpoint logic is described in natural language as an LLM prompt. The endpoints accept structured requests and return structured responses. Why is this useful? Hosted - no additional infrastructure to maintain. Prompt engineering workspace - you can edit, test and tweak…
Backengine is a hosted platform that lets users create API endpoints powered by natural language prompts instead of traditional code. Users define endpoint logic as LLM prompts, which accept structured data inputs and… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. No-code AI-powered API endpoints launched in 2023; newer entries below may have overtaken it.
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I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…
Nov 2025 · github.com · its alternatives →
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Anything API▲656Hey HN! We built Notte, a browser infrastructure and agents platform. Many of our users automate UI workflows or extract data from sites that don’t have APIs. In practice, we noticed that once an agent understands how a site works, parts of the task can often run without a browser by interacting with the same network requests the site uses. So we built Anything API: describe a browser task, and our agent explores the site, builds a function, tests it against your description, and deploys a callable REST endpoint. No infra to manage. How the build works: - Describe the task (best results come…
Mar 2026 · anything.notte.cc · its alternatives →
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BuildShip▲420Low-code visual backend builder, powered by AI
2023 · buildship.com · its alternatives →
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Swytchcode▲465Give agents reliable access to 2,000+ APIs w/ durable state
Nov 2025 · swytchcode.com · its alternatives →
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ob1 by Outerbase▲280Generate APIs, databases, and your backend with a prompt.
2023 · its alternatives →
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Arch▲314Hey HN — I’m Adil from Katanemo (with Salman, Shuguang, and Meiyu) We previously shared an early version of this project as ArchGW. Based on customer feedback, the scope expanded from “LLM routing and model access” into something broader: delivery infrastructure for agentic applications. We renamed it to Plano and reworked the architecture accordingly. The problem On-the-ground AI practitioners will tell you that calling an LLM is not the hard part. The really hard part is delivering agentic applications to production quickly and reliably, then iterating without rewriting system code every…
2024 · github.com · its alternatives →
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LLMWare▲358Dev tool to make AI apps to deploy privately or locally
2024 · llmware.ai · its alternatives →
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traceAI▲273Open-source LLM tracing that speaks GenAI, not HTTP.
Apr 2026 · github.com · its alternatives →
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Hey HN, we’re building an open specification that lets agents discover and invoke APIs with natural language, built on the OpenAPI standard. agents.json clearly defines the contract between LLMs and API as a standard that's open, observable, and replicable. Here’s a walkthrough of how it works: https://youtu.be/kby2Wdt2Dtk?si=59xGCDy48Zzwr7ND. There’s 2 parts to this: 1. An agents.json file describes how to link API calls together into outcome-based tools for LLMs. This file sits alongside an OpenAPI file. 2. The agents.json SDK loads agents.json files as tools for an LLM that…
2025 · github.com · its alternatives →
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Lorem Ipsum backends for your next no-code app, by @Draftbit
2020 · example-data.draftbit.com · its alternatives →
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The open source LLM router that connects your AI agents and harnesses to any provider in seconds. Subscriptions, pay-per-token, local models, and custom providers.
2024 · manifest.build · its alternatives →
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endpoints: /graphql /1.1 /2 /i
2023 · github.com · its alternatives →
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Hello HN, I’ve always loved building frontend-only apps—those you can prototype over a weekend, host for free on GitHub Pages, and scale to millions of users. Unfortunately, AI-enabled apps complicate things, as exposing your OpenAI key to the world is obviously a no-go. This also means mobile developers often have to run their own servers. That’s why I built ServerlessAI, an API gateway that lets you securely call multiple AI providers directly from client side using OpenAI-compatible APIs. You can authenticate users through any identity provider, like Google or Apple, and set per-user…
2024 · serverlessai.dev · its alternatives →
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Hi all, I'm currently validating an idea for a new BaaS solution which will allow you to build and host a web app backend without writing a single line of code. The app is called BackendLab and the landing page is here: https://www.backendlab.app/ The idea is that it allows you to define your database models by specifying what fields to include and BackendLab automatically creates a CRUD API which you can start using straight away. We've just launched the public beta and are looking for early adopters (free of charge, just looking for some feedback on the tool) Looking forward…
2018 · its alternatives →
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Please forgive the sign up. It means we can give away and keep track of free inference usage/no API keys needed. Happy to send sign in credentials on request if you prefer.
2025 · enginelabs.ai · its alternatives →
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I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com · its alternatives →
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The Best No-Code Backend Builder For Generating APIs
2024 · nocodebackend.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →