abhishekbasu

Joined 5 years ago

Karma
17
Submissions
45
Member since
Feb 7
prev: data scientist devising novel matching, assignment, and pricing algorithms in transportation and logistics.

now: working on ai x logistics planning, making complex decision making streamlined through the power of llm + mip.

<my webpage: $user.com> <email: me@$user.com> <linkedin: goodprediction>

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Recent submissions

Comment · 14 hours ago
agreed, this is a huge pet peeve of mine. every app that has a frontend should have screenshots on their github
Comment · 15 days ago
Thanks for sharing. Do you have a few examples of these human bottlenecks where a junior engineer is apt?
Comment · 1 month ago
Interesting read, as someone who chose not to pursue an MBA after my technical masters in '18 I wonder if there is any value aside from time to explore when pursuing an MBA in '26
Comment · 8 months ago
Thank you for your kind words! Your marketplace idea definitely sounds interesting to me, if not for payments, it would definitely provide a way to improve visibility through easier data exchange due to a common platform.
Comment · 8 months ago
Hosted on premise for enterprise, VPC for mid market customers. For enterprise customers, FDE model makes most sense for a product like this and they would assist with implementation and training. For mid market customers, I'm still exploring options to make it cost effective.

For domain-specific optimization, the value is in the solver integrations, specific constraints that form the seed, and the modular simulation that powers the visuals. The software is monetized, not the services around it.

> How will you stop LLMs from recreating it? Having worked this space for a while now I think there are two ways to ensure reliability (the real moat here), first is going deep into five-six problems that are complex enough that out of box solutions/simple prompting don't work well. Second, tightly coupling a simulator to provide rapid feedback that actually helps change manage and solve the "people" problem when optimizing operations.

Comment · 8 months ago
Comment · 8 months ago
Developing LogiModel AI (https://www.logimodel.com/) which is an agentic supply chain optimization engine that forecasts demand, optimizes operations, and simulates scenarios to reduce costs while keeping your network reliable and customers satisfied. It integrates seamlessly with your ERP and document repositories to learn your business context, then acts as an intelligent decision engine, freeing you to focus on strategy while it handles execution.

Always interested in possibilities of LLMs interfacing with MIP solvers.

Comment · 10 months ago
you're right, it should be (3,0) with optimal obj value of 6.
Comment · 10 months ago
this was a great read to start the new year! having worked extensively with mixed integer programs, it is always a bit disheartening to see them not used enough for everyday decision-making. one of my goals this year is to create a layer to make it easier to formulate mips and test them, via plain text input. this would hopefully increase adoption through a lower barrier to entry.
Comment · 11 months ago
Great product and congratulations on the launch. Who is the target user vs customer? On the surface, and I may be wrong here, this feels like a LLM layered on top of a typical AutoML structure eg: TPOT, Caret. Is that the correct mental model for a tool like this? And if so, do you see a similar problem that these tools faced in broader adoption at companies?
Comment · 1 year ago

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