What is an AI workflow? What does "embed API endpoint" mean? What is a concrete example of something I would use it for? Why would I use it as opposed to other solutions?

I'm having similar issues understanding how I might use this.

you may think of it as a cloud function, we mostly focus on HTTP based data ingestions without a storage layers. e.g. Your app is sending some data, Fleak can be used to create an API to process that data then return back to the app synchronously or save the processed data directly into a storage layer.

For someone who is not deep into AI lingo, this pretty much sounds like an ORM + Cloudflare Worker/AWS Lambda. But I'm probably really off here.

What would really help would be a concrete business case for when someone would use this and how it helps vs other options

Indeed, and no you are not off. We heard lots of feedback for building out business cases so we are will be working on that. Thanks a lot for the feedback

Maybe consider something like:

"Dynamic scaling ML based coordinator to minimize infrastructure resource costs"

Inferring the novelty of your firms value proposition would be more palatable to those that are risk averse to buzzwords. Note, simply dropping "AI" 128 times into a presentation like Intel/nvidia will unlikely work for a smaller firm.

Best of luck, =3

This is gold! practicing this pitch in front of a mirror right now. Agree on the AI part, time has changed....(we figured it was a great buzz word 6 months ago...now not so sure any more) T_T

To be honest, it's really hard to understand what Fleak does. For a minute, I thought it's a low-code way of deploying microservices/API endpoints. Maybe one end to end use case would help

This looks useful for no-code team members to create embeddings for LLM.

Since you're looking for feedback...

The "New Way" section would benefit from simplifying into a single flow chart with just two steps. Then move the existing 4 blocks to a features section.

Also would be great to have simple use cases on the landing page and link to the current Use Cases page for details. On the Use Cases page, I would get rid of the graphics. They don't convey much info and distract from the screenshots.

Maybe add a page for product comparisons. Without playing with the product first, it's a bit unclear to me how my no-code teams would prefer Fleak over their current tools (Make.com, n8n, Pabbly, Zapier, etc.).

The pricing page is somewhat of a deal breaker for my team to even spend time testing the product. The only option (free tier) seems to have really limits like 1 request / sec. And there's not enough info to understand how max events and other rate limits play together. I would keep the 1 user, 5 pipeline, token limits, and 500 requests (pipeline executions?) per month. Then remove the other limits. Alternatively, offer a Pro tier with a free month trial with higher limits.

Also on the pricing page, it would be great to list out a few use cases as examples of what's possible within the limits of each tier.

Hope this helps! And best of luck. It looks like a promising product.

Thank you for the feedback! They are truly insightful!

I have gone through Fleak's documentation and demo videos, and also ran a few demos myself. I must say, Fleak seems like a fantastic product, especially suitable for enterprise users or professional engineers in the industry. However, from a personal developer's perspective, I feel that the documentation and demo videos are somewhat too professional and not as user-friendly for ordinary users like me. For instance, as a regular web scraping engineer, I need a simple and effective way to process the data I collect. While there are some basic open-source products available that could meet my needs, the learning curve, the necessity of running a server, and additional costs (like purchasing tokens for LLM) are daunting.

If a manufacturer could provide a one-stop service, including easy-to-understand documentation, tutorials or demo videos aimed at beginners, at a reasonable price, while ensuring the reliability of the service, I would be very willing to pay for their products. I hope Fleak could consider the needs of users like us, to further optimize the product and services, making it easier for more individual developers to get started with Fleak.

Looking forward to future improvements and updates from Fleak, and continuing my support for you guys!

Thank you so much! Please consider to join our channel https://discord.gg/6YyZWGYB if you run into any issues on the free beta version! We will definitely improve and price the product in a way to satisfy individual developer needs!

I'd love something like this but with the option to bring in my own model(s). In my case I need to run BLIP2 to generate the kinds of embeddings I care about.

Ideally I'd love to be able to run arbitrary Python code in a node together with custom pip scripts to install the libraries I care about. We do some image processing steps and looks like this is not something you support.

The bias here is clearly towards text processing but I think more and more companies like this one should start thinking about multimodal pipelines.

One last point, I did not get far enough in my tests to see if I can publish a public API point secured by an API key. That's absolutely a must as having to mess around with a gateway myself to access this would nullify most of the benefits of this platform.

Thanks for the feedback! Currently we support connecting to AWS lambda functions. If you have one deployed we can definitely call it within the workflow

Also, the published APIs are publicly available, no need to configure gateway for sure

This seems like a no code platform for developing APIs. Although I am not sure if it supports all kind of data like Relational, NoSQL, Graph data etc. Also in cases where complex business logic is needed over the data, what would one implement them.

The “Docs” link goes back to the homepage. I found it hard to tell what exactly this does - how can serverless reduce overhead (usually it’s the other way around), how does it scale the LLM backend and so on.

sorry about that. Please try docs.fleak.ai directly? What Fleak offers is a simple way to capture the data processing logic, with or without LLM, and we make deployment to production with one click. That means as a user, no need to write multithread scripts, configuring clusters or create load balancers since Fleak's ingestion engine will optimize the latency across different processing unit (we call them nodes, whether it's llm or simple SQL). On the LLM side, we work with our partner to coordinate the throughput, so if there is a demand for 5000 bps Llm inferencing, we can certainly scale up to that. But for SQL functions, the users can basically get that level of autoscaling out of box.

> Does this sound useful to you?

Who is your target user?

data scientists and data engineers who do not want to deal with the server management or deploy multithreading jobs when creating data ingestion APIs.

Kind of useful but I'd generally point people to AWS StepFunctions which is a strict superset of this product (assuming they are ok with using AWS)

that's really great observation. what kind of tasks are you building with StepFunctions? We are integration partner with AWS Lambda, so definitely curious about StepFunctions too!

Isn't Langflow the better tool for LLMs?

Langflow is a great orchestration product! Our goal is to enable low latency data processing with and without LLMs through one click deployment into production ready APIs.

I suggest you try Fleak, Langflow, and LangChain to compare. Neither Langflow nor LangChain are simple options, and they are more geared towards chatbot use cases.

Disappointed I can't use an arbitrary S3 URL. I'd like to use Cloudflare R2.

I'm just one person, and I'm probably not even the target demographic, but if you're taking feedback:

I full-on laughed out loud reading your landing page for the "old way"/"new way" comparison.

It reads, to me, like "old way: easy to follow, if cumbersome, flowchart", "new way: 4 separate abstract drawings that are actually impossible to follow and do not imply any specific process is occurring."

Obviously, I'm probably in the minority here. Just some food for thought, if you're interested in that kind of thing.

Thanks for the feedback! It's harsh but very valuable!

You’re not alone. I don’t get the contrast either.

no its what i thought too and i felt like this is a tough problem especially when you get into enterprise space with a dozen heterogeneous stacks and outdated vendor APIs

if it was this easy then we would see a ton of layoffs but you can't because all these individual pieces and their idiosyncrasies cannot be streamlined and its cheaper to just have human interfaces.

So many cases I've seen where "hey this doesn't work the way it should because the vendor hired bunch of Indians who are paid by the hour didn't bother to spellcheck or use proper patterns because why would they when you pay them to bill more hours"

We'll see more and more result of negligent managers throwing third world labor at critical systems and its impact on the economy down the road. This is something only fixable by other humans and not any AI or SaaS

What are the best use cases you have built?

The common use cases we found so far are two: data tagging see https://docs.fleak.ai/1.0/tutorials/sentiment-labeling and embedding pipeline into vector store, see: https://docs.fleak.ai/1.0/tutorials/pinecone-embedding