AI · alternatives · 2026
24 alternatives to Pylar
Hey HN! We're Hoshang & Vishal, the team behind Pylar - a governed access layer between databases and LLMs. We previously led data and AI and we kept seeing the same problem across teams using LLMs internally: agents are great with unstructured data, but the moment you want them touching your actual systems of record — Snowflake, Postgres, CRMs, product DBs — everything becomes fragile, risky, or outright unsafe. Two issues show up every single time: 1. Agents over-querying They don’t understand cost. They’ll happily generate queries that blow up your warehouse bill. 2. Accidental data…
Pylar is a platform that enables secure connections between AI agents and data sources. It allows developers to connect agents to any datasource, set specific data access permissions, convert those authorized views… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 2 we have checked on their own sites, 2 of them free or with a free tier.
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Hyperterse▲86Hi HN, I’m Samrith, creator of Hyperterse. Today I’m launching Hyperterse 2.0, a schema-first framework for building MCP servers directly on top of your existing production databases. If you're building AI agents in production, you’ve probably run into agents needing access to structured, reliable data but wiring your business logic to MCP tools is tedious. Most teams end up writing fragile glue code. Or worse, giving agents unsafe, overbroad access. There isn’t a clean, principled way to expose just the right data surface to agents. Hyperterse lets you define a schema over your data and…
Feb 2026 · hyperterse.com · its alternatives →
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Open-source collaborative agentic workspace for data teams
Sep 2026 · alkera.ai · its alternatives →
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/agent by Firecrawl ▲569While building mendable - we found that feeding LLMs well-structured markdown improved accuracy. We also found it surprisingly hard. We found some great tools online, but none reliably handled the entire process. We wanted an API that took a URL, crawled the pages in the URL, and gave us an easy-to-use, up-to-date markdown we could feed into our index. So, we released an open-source repo and an API that crawls and turns entire websites into a markdown with just a few lines of code The API handles: - Crawling without consistent sitemaps - Infra to handle running many crawling jobs - Proxying,…
Dec 2025 · firecrawl.dev · its alternatives →
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Hylark▲179Dream it. Build it. Use it. Your custom workspace made easy.
2024 · hylark.com · its alternatives →
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Hi HN! We’re the team behind Fiddler, and we recently built an Agent Cache feature. It works by capturing an LLM request/response pair and, once caching is enabled, serving subsequent matching calls locally so duplicate requests never hit the provider. It’s meant to reduce three pains that show up together in agent development: token cost, feedback-loop latency, and output non-determinism. We’d love to hear your thoughts.
Aug 2026 · telerik.com · its alternatives →
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Hi HN, We're Luke and Phillip, and we're building Spice.ai OSS - a lightweight, portable runtime, built in Rust and powered by Apache DataFusion to locally materialize, accelerate, and query data tables sourced from any database, data warehouse or data lake. Phillip and I first introduced Spice on Show HN in September 2021. Since then, we’ve been schooled and humbled in every way building 100TB+ data and ML systems for the https://spice.ai cloud platform. Along with our customers, we struggled with getting fast, low-latency, high-concurrency SQL query within a budget, accessing and…
2024 · github.com · its alternatives →
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Hello HN, I don't post on here much, but wanted to get some eyes on a new project I'm just launching. I think we definitely need one more AI code agent.. I'm a long-term C++ dev, and over 30+ years I've created some successful audio dev tools (JUCE, the Tracktion DAW, the Cmajor DSP language). All of these came from me getting annoyed with something I had to use, and deciding to have a go at my own take on whatever it was. So Juggler is my attempt at an AI code agent, after spending too many hours loving what the models could do, but hating the CLI experience, and having some opinions of…
Jul 2026 · github.com · its alternatives →
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Codex Subagents▲300Parallel custom agents for complex tasks
Mar 2026 · learn.chatgpt.com · its alternatives →
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We built a model router that plugs into coding agents (e.g. Claude Code, Codex, Cursor, etc.) and intelligently sends requests to the best model to serve them. Here's a quick demo of running it locally: https://www.youtube.com/watch?v=isKhAyivtfM. At Weave, we write most of our code with AI, and it's been getting more expensive. This came to a head when Opus 4.7 was released and, thanks to its tokenizer changes, our costs shot up. We knew we didn't need Opus for everything but we didn't want to lose out on the intelligence for the cases where you really need it. So we decided…
Jun 2026 · github.com · its alternatives →
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The fastest way to build your data warehouse
2023 · weld.app · its alternatives →
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Cognitorafree▲86Built a multi-agent research system with OpenAI Agents SDK where specialized AI agents collaborate autonomously: Master Orchestrator → Data Analyst → Statistician → Report Writer Each agent has specific expertise. The orchestrator delegates tasks. All agents can execute code securely to solve problems. Example workflow: "Analyze e-commerce data" - Data Analyst: writes Python to load/clean data, spots trends - Statistician: performs significance tests, calculates growth rates - Report Writer: synthesizes findings into executive summary This demonstrates OpenAI Agents SDK's handoff system…
2025 · cognitora.dev · its alternatives →
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Alder▲22Optimizing Data Warehouse Query Performance via AI Agents
2025 · alderintelligence.com · its alternatives →
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Hi HN, Been hacking on a simple way to run agents entirely inside of a Postgres database, "an agent per row". Things you could build with this: * Your own agent orchestrator * A personal assistant with time travel * (more things I can't think of yet) Not quite there yet but thought I'd share it in its current state.
Feb 2026 · github.com · its alternatives →
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Spice.ai▲63Hi HN, we’re Luke and Phillip, and we’re building Spice.ai OSS - a lightweight, portable data and AI engine and powered by Apache DataFusion & Ballista for SQL query, hybrid-search, and LLM-inference across disaggregated-storage used by enterprises like Barracuda Networks and Twilio. With v2.0, you can add a real-time analytics node to your operational database with high-throughput native CDC replication. We first introduced Spice [1] on HN in 2021 and re-launched it on HN [2] in 2024 re-built from the ground up in Rust. In 2025 we launched Spice Cayenne [5], our acceleration and query…
2023 · spice.ai · its alternatives →
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Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai · its alternatives →
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Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers -…
2025 · github.com · its alternatives →
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Hi everyone, we are excited to share with you our new release of Data Formulator. Starting from a dataset, you can communicate with AI agents with UI + natural language to explore data and create visualizations to discover new insights. Here's a demo video of the experience: https://github.com/microsoft/data-formulator/releases/tag/0..... This is a build-up from our release a year ago (https://news.ycombinator.com/item?id=41907719). We spent a year exploring how to blend agent mode with interactions to allow you more easily "vibe" with your…
Nov 2025 · data-formulator.ai · its alternatives →
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com · its alternatives →
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Hey HN, I just spent the last few weeks building a database for agents. Over the last year I built PostHog AI, the company's business analyst agent, where we experimented on giving raw SQL access to PostHog databases vs. exposing tools/MCPs. Needless to say, SQL wins. I left PostHog 3 weeks ago to work on side-projects. I wanted to experiment more with SQL+agents. I built an MVP exposing business data through DuckDB + annotated schemas, and ran a benchmark with 11 LLMs (from Kimi 2.5 to Claude Opus 4.6) answering business questions with either 1) per-source MCP access (e.g. one Stripe…
Apr 2026 · github.com · its alternatives →
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Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
2025 · github.com · its alternatives →
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Hey HN, Automated research is the next big step in AI, with companies like OpenAI aiming to debut a fully automated researcher by 2028 (https://www.technologyreview.com/2026/03/20/1134438/openai-i...). However, there is a very real possibility that much of this corporate research will remain closed to the general public. To counter this, we spent the last month building Enlidea---a machine-to-machine ecosystem for open research. It's a decentralized research hub where autonomous agents propose hypotheses, stake bounties, execute code, and perform automated…
Mar 2026 · enlidea.com · its alternatives →
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I've been talking to founders building AI agents across fintech, devtools, and productivity – and almost none of them have any real security layer. Their agents read emails, call APIs, execute code, and write to databases with essentially no guardrails beyond "we trust the LLM." So I built AgentArmor: an open-source framework that wraps any agentic architecture with 8 independent security layers, each targeting a distinct attack surface in the agent's data flow. The 8 layers: L1 – Ingestion: prompt injection + jailbreak detection (20+ patterns, DAN, extraction attempts, Unicode…
Mar 2026 · github.com · its alternatives →
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I got tired of the overhead required to run even a simple data analysis - cloud setup, ETL pipelines, orchestration, cost monitoring - so I built a fully local data-stack/IDE where I can write SQL/Py, run it, see results, and iterate quickly and interactively. You get data lake like catalog, zero-ETL, lineage, versioning, and analytics running entirely on your machine. You can import from a database, webpage, CSV, etc. and query in natural language or do your own work in SQL/Pyspark. Connect to local models like Gemma or cloud LLMs like Claude for querying and analysis. You…
Apr 2026 · stream-sock-3f5.notion.site · 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 →