Launch HN: DryMerge (YC W24) – Automate Workflows with Plain English
179 points| samuelbrashears | 1 year ago
Here’s a video walkthrough: https://youtu.be/S4L3B21vXGY.
We initially set out to build a dev tool for API integration, and while building in the integration space, we realized existing workflow automation tools have a few key limitations. They still force users to do a lot of work like: Navigate through a sea of menus; Break down their workflow into discrete steps; Manually configure data transformations.
This led us to explore how we could make workflow automation way simpler by letting users describe what they want in plain English and having AI take care of the automation setup, replacing no-code GUIs or scripts.
Under the hood, DryMerge has two key components:
- A semantic layer that uses LLMs to interpret the user's request and map it to a series of pre-defined triggers and actions (we've built hundreds of these integrations).
- A data plane that orchestrates the actual execution, complete with smart field mapping, conditional logic, and human-in-the-loop checks.
When a user describes a workflow, our semantic layer generates multiple candidate plans, scores them, and selects the best based on prior successful/failed workflows. It extracts key entities and fields needed, and auto-generates a simple form for the user to fill in any missing details. Users can then iteratively describe, tweak, and test their workflow in the same chat.
The data plane then subscribes to the relevant event streams, executes the workflow steps, and handles gnarly aspects like pagination, retries, and rollbacks invisibly. We allow the semantic layer to delegate some values for runtime dependency injection from the data plane, to handle open-ended logic like classifying an email as urgent or summarizing a Google Meet transcript.
We integrate with 14 common services — we’d love for you to try it out and share what you think. Check it out at https://drymerge.com/app.
techietorontos|1 year ago
FYI: In good faith, I asked some simple javascript questions and stuff like "who is michael jordan" and got answers from the LLM. Perhaps adding some additional guardrails to ensure queries are workflow based could save you some tokens.
Great work!
edwardfrazer|1 year ago
philjr|1 year ago
djyaz1200|1 year ago
samuelbrashears|1 year ago
keepamovin|1 year ago
In order to display / faciliate the human-in-the-loop drop-ins you may be interested in BrowserBox to provide an interactive (and multiplayer) web browser you can embed in your web app. You can check out a demo of it live here: https://browse.cloudtabs.net/signupless_session
thoughtlede|1 year ago
1. For dynamic injection of arguments in your data plane, do you use LLMs?
2. What did you find you cannot do yet because of LLM limitations (and not because of lack of third-party integrations)?
3. I haven’t looked closely into your product, but is every “effect” of a workflow something that only the requesting user can see? Is this how you ensure bad or wrong things are not hurting other people or systems that are outside of user’s control?
samuelbrashears|1 year ago
2. Anything too complex (e.g. 5+ steps) tends to be unreliable. Also, any workflow where potential failure/unexpected behavior is too risky to leave up to an LLM.
3. The only actions we take are with our user's tools, so many workflows are simply organizing their information between their apps. However, e.g. gmails could be sent externally so we have guardrails/sanity checks to mitigate risk there.
Redster|1 year ago
edwardfrazer|1 year ago
lecha|1 year ago
edwardfrazer|1 year ago
Octopuz|1 year ago
I would appreciate 'whenever I post on X or Mastodon add this to a sheet and put text and URL in its own column'
samuelbrashears|1 year ago
fuddle|1 year ago
edwardfrazer|1 year ago
Aaronstotle|1 year ago
Edit: Homepage link https://drymerge.com/
faitswulff|1 year ago
hubraumhugo|1 year ago
With GPT-5, we might see similar capabilities where integrators would simply provide relevant APIs and documentation, while the AI figures out the automation steps and orchestration.
Plugins and custom GPTs were early (failed) attempts in this direction.
CharlesW|1 year ago
FYI, Microsoft's adopting AI for natural language authoring and other capabilities into Power Automate. https://www.microsoft.com/en-us/power-platform/products/powe...
edwardfrazer|1 year ago
nicknow|1 year ago
edwardfrazer|1 year ago
camwest|1 year ago
In my experience a lot of people don’t know how to write with a level of specificity needed to map to pre defined triggers.
For example: instead of saying spreadsheet they may say “roadmap” or instead of saying “Notion database” they may say “bug tracker”
This stuff fails in Zapier.
Any chance you handle those cases better?
edwardfrazer|1 year ago
We think one of the big differences between Zapier and DryMerge is that we abstract a lot of the data flow/configuration away from the user, which lowers time to value and lets us do cool semantic filtering and other LLM-powered backend stuff.
samuelbrashears|1 year ago
toddmorey|1 year ago
edwardfrazer|1 year ago
iot_devs|1 year ago
Basically smart filters for gmails and Outlook.
You got to express in plain English which email to filter on and how to create a DRAFT and the tool automatically filters your email and generates drafts or add labels.
It was born out of frustration of replying to several emails, all the same, with content that was already available online. Still need to provide a human and technical-ish touch.
Demo video on: https://m.youtube.com/watch?v=ALQNDYjLQUU
https://getgabrielai.com
aitoehigie|1 year ago
edwardfrazer|1 year ago
babyshake|1 year ago
edwardfrazer|1 year ago
DryMerge differentiates by focusing on plain english chat as an interface. The reason that's important is because it's accessible to more non-technical folks, lowers time to value (a lot easier to say what's on your mind than drag & dropping/building), and allows for cool semantic filtering like "Angry emails", "Investor", or "Potential customer" which we've found opens up a whole bunch of cool new possible automations. We also heavily focus on event-driven workflow automation (we have a lot of triggers).
tmaly|1 year ago
toomuchtodo|1 year ago
(imho, two cents)
frankdenbow|1 year ago
shmichael|1 year ago
samuelbrashears|1 year ago
einarvollset|1 year ago
edwardfrazer|1 year ago
nextworddev|1 year ago
mahsima|1 year ago
Cilvic|1 year ago
edwardfrazer|1 year ago
luckydata|1 year ago
flanbiscuit|1 year ago
I am not affiliated with them, was just curious on what your experience was.
bugbuddy|1 year ago
voiceblue|1 year ago
「毎時、おもしろいミームのリンクを送ってください。」
This also works just fine:
मुझे रोज़ दो चार चुटकुले ईमेल कर देना।
edwardfrazer|1 year ago
timr|1 year ago
unknown|1 year ago
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teaearlgraycold|1 year ago
edwardfrazer|1 year ago
rotrixx|1 year ago
aster0id|1 year ago
This is why I feel new startups that are trying to disrupt established tech companies using LLMs are doomed/have no moat or technical advantage. Incumbents have the manpower and distribution to replicate everything in house. Not to mention the incentive to add "AI" to their service description which will boost their valuation automatically.
samuelbrashears|1 year ago
jaggederest|1 year ago
swalsh|1 year ago
mangocheetah123|1 year ago
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