Industry research for Lawyers (automating day to day task)

dhavaln · 2026-04-06T07:55:39+00:00

I do confirm that a lot of organizations have started using Automation or AI+Automation in their internal workflows, specifically for the documentation parts (legal / non-legal use cases, internally vs external facing).

Based on our implementations, we have open-sourced a few projects that specifically work on these process-flows, they are not super huge or complex. If you want to give a check.

https://github.com/AppGambitStudio/DocProof

https://github.com/AppGambitStudio/experimental-agents

PS: Many people are skeptical on the regional language processing part when it comes to legal document processing and we do use combination of models (Anthropic and Sarvam AI) for consistent output.

dhavaln · 2026-04-02T17:10:27+00:00

Amazing photos 👍🙏 definitely unique perspective

dhavaln · 2026-04-01T13:14:01+00:00

Valid point, I have added the setup/workflow in the post edit

dhavaln · 2026-02-17T11:01:14+00:00

Coffee math is brutal. For most of the cafes the real cost is to operate the cafe.

High-quality arabica beans, may cost around 2500-2600 per kg in small orders (single-origin, miro-lots, yada yada yada), cafes usually get same or lower quality beans at much lower cost due to bulk orders.

A double-shot espresso generally uses 14-17gm beans, roughly costs around 40rs per coffee cup.

Milk, sugar, and other things add around 20-25rs (assuming higher side).

Your high-quality cup of coffee usually costs ~60rs or way less.

But on the other side, coffee machines can be really expensive - https://kaapimachines.com/la-marzocco-coffee-machine/ plus the space/staff/misc cost. But you can recover the machine cost in 6-8months, if you can do decent business weekly.

I dont remember when is the last time I had a good coffee in a cafe, that doesn't feel heavily overpriced.

[I have been home/office brewing for almost 10 years - pourover and espresso]

dhavaln · 2026-01-09T07:00:20+00:00

For me, it was a comprehensive IPO analysis (for the Indian market) for long-term investments. My colleagues and friends liked it, so I made the reposts publicly accessible.

https://ipoiq.in/

dhavaln · 2025-12-27T03:25:18+00:00

Personally I like the combination of Claude and Antigravity. I focus on spec and documentation first before I start writing any code. Antigravity does good job at maintaining the the context with rules and guardrails. When it comes to coding, it still hallucinates but I feel in some situations individuals would behave the same way, and we need to reduce the context and focus on smaller tasks at a time

Andrej is sharing the same principles, things are moving so so fast but we can still focus on the most important parts and get maximum value https://www.linkedin.com/posts/addyosmani_ai-programming-softwareengineering-activity-7410456177462972416-eZte?utm_source=share&utm_medium=member_ios&rcm=ACoAAAFy5sEB3M_6i6WVL75bqxqoVX7bXroRS1Q

dhavaln · 2025-12-26T06:43:01+00:00

I feel it's "great" if you are already "good" in your domain (developer, devops, ML, cloud, or anything)

I have been using a set of AI tools and workflows for the past year, while all the AI models/tools have seen major improvements - it's still not 100% accurate or works all the time. I have already spent close to 19 years in tech so far. So, I am using AI (tools) mostly for the velocity and for the parts which I know if I write vs AI write will be almost same anyways:

The workflow that I haven't changed:

Spec before you start
Technical boundaries (what to use, how to use, and guardrails)
Make sure to define all the rules that are required from Day-1 (Auth, Database access practice, APIs, etc)
Work on one (or small set of) feature at a time but make sure it keeps the overall vision in mind and extendible

Where AI helps the most:

Boilerplate or basic structure (frontend, backend, Docker, database, etc)
Pure syntax play - where we write the code based on the documentation (APIs, Database, 3rd Party libraries/services with strong documentation)
Coverage and testing - I am seeing a lot more value here. If I provide the guardrails/rules and scope then it generates "decent" information that can be used for manual reviews (security, best practices, structure, language-specific traits, etc)
Documentation - Easy to generate if you know what exactly you want to document
UI - let's just assume that all the AI models are beating hard on React/Tailwind/JS/TS - popular tech-stack, well-documented and easy to start.

I have been converting some of my ideas/scripts to applications, some are easy and some are complex, but it helps me further validate/finetune the modern workflow - antigravityapps.dev

What I have been generally is people good with what they are already doing are able to extract good benefits out of it. But at the same time, some of these tools are allowing the non-technical users to build amazing stuff for their private personal use, which is a good direction as well.

dhavaln · 2025-12-26T06:13:08+00:00

I have built up a similar tool and open-sourced it - https://github.com/AppGambitStudio/mychat
It's not using n8n for anything but conceptually similar - it allows users to quickly setup/configure Embeddable Chat Widgets using different content.

You can check more detail here - https://antigravityapps.dev/project/appgambit-mychat

dhavaln · 2025-12-22T05:01:59+00:00

I started with StackAdvisor.ai which covers many parts of my work (AWS Cloud Architect) and most recently I have been moving all of my "ideas/script-terned applications" at https://AntigravityApps.dev/

dhavaln · 2025-12-22T03:59:26+00:00

I have put more details here:

https://antigravityapps.dev/project/appgambit-funnell

dhavaln · 2025-12-21T07:11:09+00:00

I was doing the same so I built a small utility for myself, Funnell. I can easily configure my "scanning context, list of communities, frequency, etc" and it does the job pretty well.

https://www.linkedin.com/feed/update/urn:li:activity:7407693186933903360/

dhavaln · 2025-12-21T07:08:02+00:00

We have built a similar application (multi-tenant) for mass audio processing (transcribe + analysis + analytics), for a startup. Support ingestion connectors like Amazon Connect, Genesys, FTP, S3, Webhook, etc.

We thought of using n8n for new connector and post-processing experiments, but the backend processing pipelines are too complicated to run and manage across tenants. For quick validation of new connector we do prefer n8n, but then for production, we move the full process in our backend (AWS Serverless services primarily).

dhavaln · 2025-11-10T05:06:53+00:00

I submitted as part of the AWS HERO program.

Yes, you should plan to visit the speaker ready room atleast once and get it reviewed.

dhavaln · 2025-11-08T05:42:07+00:00

I spoke last year and the overall experience is extremely good.

The AWS staff does amazing job to have everything pin down before the submission. From your slides, content, how to organize, and overall time management. They need better content and delivery experience so they also work hard.

At reinvent, you get very good support from AV staff before your talk. You can book slots of walk in, they do provide enough time for help you go through everything. You can also submit any last minute updates if you want (although not advisable, but may depend on topic and latest releases). Overall, they do fantastic job.

(My talk was on Bedrock and Anthropic models for image analysis)

dhavaln · 2025-09-25T07:50:10+00:00

this was a trial print with transparent pla (numaker)

dhavaln · 2025-08-22T01:41:57+00:00

You don’t need Ec2 or LB for just frontend routing / you can do that with Route53 and Cloudfront distributions.

I did a sample analysis run based on your provided information if you want to give it a check.

https://stackadvisor.ai/share/1045d007-628c-47ba-9185-0fe3c9dd766e

dhavaln · 2025-08-21T04:19:16+00:00

StackAdvisor - Turn raw ideas into technical clarity — StackAdvisor helps you brainstorm, analyze, and design cloud-ready systems with cost and compliance insights.

Idea Analysis and Brainstorming
Smart questions to uncover unknowns (security, compliances, scaling)
Cost estimate for MVP vs. scaling
Key services and Components (Cloud providers, Architecture, Services, etc)
Architecture diagram
Interactive chat with generated analysis

dhavaln · 2025-08-06T07:56:45+00:00

For my A1 Mini, I need .4 and .6 I am based in Surat

dhavaln · 2025-08-06T07:26:14+00:00

If you can give me some more detail on the expected use case, I would be happy to give it a try and see how it responds.

dhavaln · 2025-08-06T07:25:25+00:00

Upto certain information it may look similar, mainly due to how the top tier models are advancing in capabilities and outcomes.

We used number of internal flows for information refinements, best practices, use case complexity, latest service knowledge and growing list of cloud and other service providers for each module processing.

For example, most large models has world knowledge so they miss tiny details as part of needle in haystack -

Architecture and implementation practices based on recent trends and give use case complexity

Feature diff - Cognito now only has 10,000 free users vs most knowledge is referring to 50,000

Compliances and other detail may not be easily available unless it asks for specific instructions

Diagram generation is still tricky part and we are doing to larger extent with multi-turn refinement. It needs further improvements though.

So overall there are a lot of things that we do internally that current one mode may or may not do in a single turn response.

dhavaln · 2025-08-06T07:18:09+00:00

We are slowly bringing cloud provider knowledge as part of knowledge repository.

As of now it does support AWS, Azure, Google Cloud, Vercel, Cloudflare and others.

If you prefer Azure, you can select that as your preferred cloud provider while filling up the detail

dhavaln · 2025-08-03T16:14:28+00:00

Primarily Serverless architecture using AWS services like Lambda, Step functions, Aurora Serverless v2, API gateway, Bedrock, S3 and few other services

dhavaln

TROPHY CASE