alt.hn

3/13/2026 at 3:45:33 PM

Launch HN: Captain (YC W26) – Automated RAG for Files

 https://www.runcaptain.com/

by CMLewis

3/13/2026 at 5:08:41 PM

Having tried this a bit I do really like the single api call for all of it.

I also appreciate transparent pricing but I am not 100% sure the sense of scale of costs. It could be helpful to give some ballparks on things for each of the plans. I'm not sure exactly what i could get out of a plan. My guess, trying hard to figure it out, was if i had about 1,000 pages of new/updated content per month, I would pay $295/month for unlimited queries on top of it. Is that roughly correct?

by mchusma

3/13/2026 at 5:52:27 PM

Yes, we don't charge for queries. For $295, you're able to index up to 1000 pages of new content per month into a fully queryable pipeline.

Advanced and Basic do play a difference though. Advanced is for complex graphics or charts in the documents submitted. Basic is sufficient for most document workloads.

by edgarbabajanyan

3/13/2026 at 4:43:42 PM

Good looking! I didn't get to watch the video or look at docs in depth, but do the results trace back to the location of the answers in a document? Let's say it finds an answer in a PDF, and I'd like to know where in that PDF the citation is. Is that possible or intended?

by vg_head

3/13/2026 at 6:54:07 PM

This is an interesting product, thanks for sharing. Can you elaborate on some of your competitors in this landscape and what you might do differently compared to each one?

by jzig

3/13/2026 at 10:42:08 PM

Thanks! The largest alternative to Captain is folks trying to build file search themselves. As mentioned in the post, it is a lot to manage.

The most similar product I've seen is Vertex File Search. They're hosted inside of GCP which can fit nicely into existing cloud deployments. Captain indexes from more sources (like R2 for example) and anecdotally provides faster indexing.

by CMLewis

3/14/2026 at 5:02:00 AM

Hey, congrats on the launch..

How do you compare to kapa.ai ? I have tried them.. and on search quality, they are really impressive.

by freakynit

3/14/2026 at 12:29:46 AM

What about OpenSearch, Onyx, Glean Search, Kore.AI, Sana Labs?

by jzig

3/14/2026 at 3:35:23 AM

OpenSearch provides general search infrastructure and they recently added vector search. It's a low level engine so users would still need to build their own ingestion, parsing, chunking, embeddings, re-ranking, permissions, etc.

Onyx, Sana, and Glean are closer to application-layer enterprise AI products. Their internal knowledge assistants can search across SaaS tools but the interface is more graphical and seats are purchased as end-user software.

Captain sits in between because it's an API-first retrieval system to fully-manage file workloads. This adds search capabilities to existing AI agents but the agents are managed by the developers, outside of Captain.

Kore.ai however is more of an agent platform. Their focus is building and orchestrating agent workflows (which can include document retrieval, but that's not their main focus).

by CMLewis

3/15/2026 at 3:37:07 PM

You ought to also look at AWS Kendra GenAI Index + AWS Bedrock retrieve_and_generate().

The cost is insane but its dumb simple

by whattheheckheck

3/13/2026 at 4:25:20 PM

This is cool, like qmd as a service with real-time integrations where it matters?

How do you handle more structured data like csv/xlsx/json? Would be cool if it were possible to auto-process links to markdown (e.g. youtube, podcast, arbitrary websites, etc) a la https://github.com/steipete/summarize (which can pull full text in addition to summarizing).

by jamiequint

3/13/2026 at 4:37:51 PM

Thanks, we're just starting to optimize more for the semi-structured data. So far, we've been parsing tables into Markdown and running them through the contextualized embedding model with no overlap, taking advantage of how it strings together chunks. This isn't great for big files so we're exploring agentic exploration (slow but good for more structured numerical data) and automated graph creation (promising for more relational data).

Love the auto-process markdown idea, we'll add it to our roadmap :D

by CMLewis

3/13/2026 at 10:31:54 PM

Great name - Captain Hook recently hit public domain - would be a sick logo! (Disney stuff like red jacket still copywrited)

by sjkoelle

3/13/2026 at 10:45:16 PM

No way, that's awesome!

by CMLewis

3/14/2026 at 2:10:18 AM

I think I've lost count of how many of these start ups I've seen. But what I really cant fathom is that pricing which is completely out of band. You can already talk to files directly with gemini, just wrapping other apis etc makes no sense. This is even stuff now you can easily codegen entire solutions for esp object storage based ones. Don't see actual any value add or differentiators here. It's obviously not that secure, and ingestion pipeline/connectors are also commodity.

by bfeynman

3/14/2026 at 3:45:51 AM

You're right that you can chat with files using Gemini or a codegen'd RAG pipeline, and that does work well for a lot of teams.

The problem that Captain really addresses comes when production pipelines need to run continuously over large file corpora with fast, incremental indexing, and reliable latency. The maintenance required in these situations is often quite significant.

Captain focuses specifically on making sure the retrieval layer can operate smoothly so folks don't have to scale & maintain the infrastructure themselves.

by CMLewis

3/14/2026 at 5:14:24 AM

For use cases where the increased value ~= 20%, the cost of the distraction with that low of a margin is a hard sell. (Just based on your intro, that was my read)

No disputation of the core idea, I think you are on the right track, but the pitch isn't compelling. People looking for these kinds of AI solutions tend to favor simplicity and ~80% is fine, because the overall perceived productivity improvement is 5-10x, with such wide error bars that the approximate gain is just not worth maximizing for right now.

You might be a few months-years early, or target people who have maxxed out because they cannot retrieve from their second brain effectively. Most folks I've talked to are just trying to keep up, optimization/efficiency is not on their radar.

by edmundsauto

3/14/2026 at 12:13:49 AM

Its a nice thought & the outcome as a product. Why would an organization pay for such product, as they can very well build a RAG these days tuning to their business needs. I see that Captain API does everything in one shot without rebuilding the RAG, but why would an organization to pay for this solution as this entire chain of activity can be automated and run at non business hours as a batch with the fraction of a cost. What's the delta efficiency that captain would bring it to the table , have you done any benchmarks, if its negligible, i see no reason for any organization to use the captain

by macieman

3/14/2026 at 1:48:26 AM

Congratulations on the launch, Edgar and Lewis! I tried out https://pg.runcaptain.com/ --- 1. I can't seem to select the text during text generation without it being deselected as soon as more text is generated.

2. It seems like it tries to emit citations, but doesn't emit proper links and instead just wrote [filename].

> one of the most common pieces of advice Y Combinator gives to startups [153_do_things_that_dont_scale.pdf].

by desmondwillow

3/14/2026 at 4:10:52 AM

Thanks for trying it out!

Yeah good catch on the demo. If this were a production deployment, the citations would be hyperlinked to object storage. Captain is just the index, so the real files would be wherever they were indexed from.

by CMLewis

3/13/2026 at 11:33:45 PM

Just a note on the website, I thought at first my browser had been hijacked by a shipping or travel agent. The first impression is how AI has improved ship tracking, so you can now track ships with 98% accuracy, with little to no hint this is AI infrastructure until you scroll down.

If you know what Captain is, this is not an issue. I closed the browser tab at first, thinking "what the hell is this, I don't give a damn about shipping forecasts"

by Perenti

3/14/2026 at 4:17:18 AM

I see what you're saying, we may tweak the hero to make it a bit clearer. Thanks for the note!

by CMLewis

3/14/2026 at 5:23:19 AM

You're welcome. By the way, as an AIdiot, anything that makes RAG less brittle is good.

by Perenti

3/13/2026 at 10:38:30 PM

The problem with these kind of tools now is that Codex is so good you can basically build something which is good for 99% of cases in a single day, and it's free...

Look at Tobi vibe-coding QMD, he's not a full-time engineer and vibed that up and now it's used as the defacto RAG engine for OpenClaw.

by saberience

3/13/2026 at 11:23:55 PM

Yeah QMD is quite impressive! The main difference between us and them is the scale folks would be looking at indexing. The serverless ingestion engine I described in the post is optimized for processing large batch jobs with high concurrency. We depend on a lot of cloud compute for this which isn't something QMD's local-first environment is optimized for. That said, it's a great option for OpenClaw!

by CMLewis

3/13/2026 at 11:05:09 PM

Funny you say that.

I spent the last two days building this exact thing for our internal use.

Managed to get a full RAG pipeline integrated and running with all of our company documents in less than two days work.

Chunking, embedding and querying, connected to S3 and Google Drive, and running on our own hardware (and scaling on AWS too if needed).

by eckesicle

3/13/2026 at 9:24:26 PM

Congrats on the launch. Very quick feedback on the site, since I usually try to check out the blog section, https://www.runcaptain.com/blog layout is broken in mobile, I tried brave/chrome/Firefox.

by alexhans

3/14/2026 at 1:59:26 AM

Thanks, just shipped a fix ;)

by CMLewis

3/13/2026 at 6:39:44 PM

Are you writing the integrations listed there, or is are you using something that manages the data connections?

by BoorishBears

3/13/2026 at 7:00:58 PM

We've built these integrations ourselves.

For larger enterprises that require governance and additional compliance, we've been relying on trusted partners to help establish a connection to Captain

by edgarbabajanyan

3/13/2026 at 6:13:06 PM

Just some unfiltered feedback after checking out the website: from what I understand this is an SaaS only? So basically I’m asked to upload ALL company docs to a company that existed for basically a minute with some questionable SOC2 report. Soc2 is basically dead as a security artefact and the data asked to upload is sensitive by nature. I don’t see that working.

by cleansy

3/13/2026 at 6:24:48 PM

> Soc2 is basically dead as a security artefact

can you expand on that?

by piker

3/14/2026 at 2:10:49 AM

not to mention they are using 3p apis for everything.. gemini, reranking etc...

by bfeynman

3/13/2026 at 4:26:18 PM

> spotty RAG

:O

by jzig

3/13/2026 at 6:43:17 PM

Interesting to see still solutions being developed for RAG. We developed a solution similar to yours: Automatic indexing from GDrive, SharePoint etc. and then advanced hierarchical chunking, context header based markdown conversion etc... All the tricks that were published last year while RAG was still the "new" kid in town. We finally open sourced everything as the competition from the big players (Notion AI, Google etc.) was daunting. If anyone is interested, this blog post about all the techniques we tried and what actually works is still relevant and up2date: https://bytevagabond.com/post/how-to-build-enterprise-ai-rag...

by maxperience

3/13/2026 at 8:13:01 PM

Thank you so much for this, started reading it a few min ago and already learnt quite a lot!

I like how clean and compressed the info is

by macmac_mac

3/13/2026 at 6:09:53 PM

[flagged]

by BrianFHearn