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Modular

drop AI features into your app with two function calls

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I kept hitting the same wall at work every time we needed to ship an AI feature. What looked like a week of work turned into picking a model, setting up a vector DB, managing embeddings, wiring up chat history, handling retries — none of it was the actual feature. So I built Modular. You register a function that returns your app's data, then call ai.run() for one-shot features or ai.chat() for stateful conversation. Everything else — context management, embeddings, session history, model routing, retries — is handled. MCP-native from day one. Works with Claude, GPT-4o, and Gemini. Still early — collecting feedback before building the full SDK. Would love to hear if others have hit this same wall, or if you think I'm solving the wrong problem.

HN · launched Apr 20, 2026 · 7 upvotes (top 61%) · 0 views

Niche: ai software development platforms · 128 launches, 10 in the last 7 days ▼ -41% · Explore this niche →

Category and tags
  • Horizontal
  • Dev tools
  • Developer
  • AI-native
  • Commercial product

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More like this: all 128 launches in ai software development platforms →

Could you build this?

Yes It acts as a wrapper SDK/backend service coordinating LLM calls, vector embeddings, and conversation session persistence behind a unified API.

Discussion

1 comment analyzed.

Concerns raised: No SDK yet, still very early stage, Uncertainty about market need/validation

Feature requests: SDK availability

Competitors

Other products that read as similar to this one : 280 launches clear the similarity bar, closest 8 shown.

Attention rank: #158 of 281 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 173 days after the earliest competitor.

Related data

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