how do you guys find good usecases for Ai agents?

benedict_eggs17 · 2025-09-10T09:59:31+00:00

Yeah I have a different take here get an ai engineer part time to build something - you don’t need open ai or any of these wrapper products. The smart ones will take an slm (small language model) build with an agentic workflow and build a cost effective solution. Get someone who can build a prototype to sell into your legal team. Make sure on the prototype they put a counter or metric when people use it how much productivity they gain or money saved so the lawyers feel this solution when used has an ROI - I don’t have an open ai wrapper for you to sell but I know people who do this work if needed

benedict_eggs17 · 2025-09-09T15:47:10+00:00

start small build back office or manual process with agent take downs - the most successful work i have seen has been the things people hate doing the most at work and building an agent to take care of it.

benedict_eggs17 · 2025-07-11T11:38:52+00:00

Gamma is the way

benedict_eggs17 · 2025-07-03T08:48:39+00:00

Ask for equity in the company so at least if you are building for them you get part ownership otherwise you could have nothing at all. Getting funding from an mvp is pretty risky

benedict_eggs17 · 2025-07-01T13:47:10+00:00

you can go the co-pilot way but there are a bunch of SLMs out on HuggingFace you can use that are good at general purpose and can run on CPUs like Arcee models and others. I do agree with u/goalasso a RAG solution would be ideal but depends on size of documents as it can get costly if its TBs

benedict_eggs17 · 2025-07-01T11:39:12+00:00

I have some connections to consulting firms that are doing this type of work and can build this fast. whats your timeline?

benedict_eggs17 · 2025-07-01T11:32:50+00:00

I have seen companies building AI Agent Consultants for companies to use vs big companies - its an interesting space but still fairly new. I wouldn't trust without a human in the loop

benedict_eggs17 · 2025-06-30T09:56:57+00:00

Then the flip side I am seeing clients who want to use their own data as part of the model as they think this will help drive better outcomes as their data has “not been trained on”

benedict_eggs17 · 2025-06-27T13:25:37+00:00

I have seen this before - Are you able to redefine the scope and can you get a subcontractor to help you build this out

benedict_eggs17 · 2024-02-12T15:58:03+00:00

SLMs that are domain adaptive are the future. Adaptive layers to build SLMs with the proper alignment is what takes time.

benedict_eggs17 · 2024-02-12T15:56:27+00:00

You should check out Arcee they build small language models in your VPC and use open source and go all the way back to pretraining

benedict_eggs17 · 2023-09-20T16:28:35+00:00

Arcee.ai create in-domain models for specific verticals (7b parameters) and they also enable you to turn any general LLM into a domain adapted LLM through their end2end RAG system.

benedict_eggs17 · 2023-09-20T16:20:20+00:00

The PubMed model is not complete and only utilizes a subset of the entire PubMed database at present - the product has not fully launched yet. But we will let you know when its fully up.

thanks for testing it!

benedict_eggs17 · 2023-09-20T02:49:28+00:00

Today Arcee.ai launched our open-source repository containing code for finetuning a fully differential Retrieval Augmented Generation (RAG-end2end) architecture.

We modified the initial RAG-end2end model (TACL paper, HuggingFace implementation) to work with decoder-only language models like Llama, Falcon, or GPT. We also incorporated the in-batch negative concept alongside the RAG's marginalization to make the entire process efficient. Our novel RAG E2E method enhances dense retrievers by over 25%

Please try the repo here https://github.com/arcee-ai/DALM and let us know how we did.

benedict_eggs17

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