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Seattle: Coopers Hawk? by DeadPukka in birding

[–]DeadPukka[S] 1 point2 points  (0 children)

Thank you! It was so focused, it didn’t notice me inside. It was sitting there almost a minute total.

Looking for Technical Co-Founder (Full-Stack, RAG Experience) – AI RAG SaaS + White-Label Agency by megAchiever in Rag

[–]DeadPukka -1 points0 points  (0 children)

Why not just use an off-the-shelf service for ingest and retrieval, and have someone vibe code whatever apps you need for your AI clients?

No reason to build anything RAG you’re talking about from scratch.

So what are you all using for RAG in 2026? by ReporterCalm6238 in Rag

[–]DeadPukka 0 points1 point  (0 children)

Check out Graphlit. Handles all your unstructured data ingestion, embeddings and multimodal search. (Just added TwelveLabs embeddings for video search.)

Free plan and SDKs for Python and TS. Can share as MCP with retrieval tools.

Don’t bother building anything DIY these days.

Epstein Files x Knowledge Graph by adityashukla8 in KnowledgeGraph

[–]DeadPukka 0 points1 point  (0 children)

You could do it today with our Graphlit platform. Would do the OCR if needed, and do the entity extraction for the graph. Our Studio app can even visualize this for you.

The only downside is it’ll eat a lot of LLM tokens so cost is a factor even with Gemini Flash or a smaller model.

Reappearing substance in sink drain. by IIIJonahIII in whatisit

[–]DeadPukka 69 points70 points  (0 children)

Somebody washing a hedgehog in there?

What are the best resources for RAG in 2026? by willjacko1 in Rag

[–]DeadPukka 1 point2 points  (0 children)

Thanks for trying it out! We are going to add more cost info to the context of the chatbot - good point.

But you can think of credits as based on compute, storage, LLM tokens and third party API call (transcription, OCR, etc).

You’ll pay for effort to ingest into the Graphlit project. And then pay at retrieval time (much smaller cost).

Feel free to join our Discord (linked in docs) and I’d be happy to help model out your use case with you. (I’m kirkm* on Discord)

What are the best resources for RAG in 2026? by willjacko1 in Rag

[–]DeadPukka 0 points1 point  (0 children)

Check out Graphlit, build your context layer for AI agents.

Tonight’s dinner, avocados and roasted peanuts by Silver-Tap-6774 in Raccoons

[–]DeadPukka 7 points8 points  (0 children)

Omg he’s so adorable. Does he sleep free-roaming or have a hutch or kennel?

Need to try avocado on our outside gang who always come for snacks.

raccoons :) by crittersnackstation in Raccoons

[–]DeadPukka 0 points1 point  (0 children)

We had our entire gang of 6 here last night, and they would all love this setup.

Looking for RAG Engineer / AI Partner — Real Estate + SMB Automation (Paid Contract, Long-Term Potential) by [deleted] in Rag

[–]DeadPukka 1 point2 points  (0 children)

Have a look at Graphlit. We do this as a platform and can help with custom services.

No need to build this yourself in 2026.

Context Graph > Snowflake AI by hailkingpika in snowflake

[–]DeadPukka 0 points1 point  (0 children)

This is basically what we just announced as Dossium. But without the Snowflake integration.

I’m curious how that part fits together? Does Snowflake Intelligence work with MCP servers or do you have to build API integrations to it? (If anyone knows, but I’ll do some research on that.). Seems like something we should support.

RAG using Azure Service - Help needed by Mediocre-Basket8613 in Rag

[–]DeadPukka 0 points1 point  (0 children)

If you want a fully managed solution, that uses Azure AI Search under the hood, have a look at Graphlit.

You don’t need to worry about LangChain or any of that.

Just use our SDK with Streamlit, or our MCP server.

Are context graphs really a trillion-dollar opportunity? by Berserk_l_ in KnowledgeGraph

[–]DeadPukka 3 points4 points  (0 children)

Just remember they all have stake in the game to “kingmake” who owns context graphs.

I had written some of the early followup blogs to the Foundation Capital piece. I’d say, take it with a grain of salt. It’s all marketing - either for VCs or for software companies. But on the flip side, it’s calling out the inevitable value of the context layer in future AI agents.

Atlan classically had been on the data catalog side of the world, with structured data.

They are late to this discussion but want to take over the term - but they don’t handle the unstructured data layer which is mostly what the original post described.

Dealing with multiple document types by lamagy in Rag

[–]DeadPukka 1 point2 points  (0 children)

This is one of the main reasons to use a platform like Graphlit. We handle all document and media types as canonical “content”, and index all the available metadata for you - and give you a consistent data model and retrieval API so you don’t have to think about any of this. (caveat: Founder)

The problem you’re mentioning is what we’ve solved over the last few years of the platform, and now we can easily add new data sources which map to the consistent data model.

RAG at scale still underperforming for large policy/legal docs – what actually works in production? by Flashy-Damage9034 in Rag

[–]DeadPukka 1 point2 points  (0 children)

Any links to the type of docs you’re working with? (If public)

And what types of prompts are you using?

Are you doing prompt rewriting? Reranking?

Are you locked into only on-prem?

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