Alternatives
Products that do what LPMR Delta does
Audited financial data, minus the heavy terminal
- 1
- 2
- 3
- 4
Instantaneous bank statement PDF parsing and fraud detection
2022
- 5
- 6AN
When building workflows that rely on LLMs, we commonly use structured output for programmatic use cases like converting an invoice into rows or meeting transcripts into tickets or even complex PDFs into database entries. The model may return the schema you want, but with hallucinated values like `invoice_date` being off by 2 months or the transcript array ordered wrongly. The JSON is valid, but the values are not. Structured output today is a big part of using LLMs, especially when building deterministic workflows. Current structured output benchmarks (e.g., JSONSchemaBench) only validate…
Apr 2026 · interfaze.ai
- 7
- 8
- 9
- 10
- 11
- 12NA
2021 · try.herondata.io
- 13
An interactive Power BI terminal to track subscription risk
May 2026 · github.com
- 14
- 15
Hi, Wanted to share something I've been working on for over a year. AuditBadger is a compliance management platform that uses AI to write policies (there are underlying "templates" with basic requirements), rewrite controls (or trust service criterions) to match the company context, help figure out your own controls, does initial risk assessment, and business continuity planning (which at least gives you an example of how the process should look like). Fun fact - I wanted to share this a year ago, but then I spotted something similar here. The most common comment was about lacking the SOC 2…
Aug 2026 · auditbadger.com
- 16UM
I've been exploring uses of file metadata. Here's an interesting one with a legitimate (and potentially unreliable) use case. Focuses on ease of use. Would love to hear feedback.
2023 · github.com
- 17PE
2016 · pasteql.com
- 18VT
Post-Opus 4.6, LLMs feel much better at using bash, code, local files, and tools. So I kept coming back to a simple question: if a model can use a computer reasonably well, why can’t I just give it my broker account, a strategy, and let it trade? My conclusion is that the blocker is not model capability in the abstract. It is the system around the model. A raw LLM breaks on a few practical things almost immediately: • no persistent operating memory across sessions • no trustworthy record of what it did and why • no hard approval boundary before money moves • no cheap always-on monitoring if…
Mar 2026 · github.com
- 19
- 20
- 21IB
Apr 2026 · github.com
- 22
- 23
Hi, my name is Kam, and today my cofounder Josh and I are shipping Finterm, a CLI that gives coding agents direct access to financial data: stock prices, options data, SEC filings, and Ticker Deep Research, a filtered ticker news search. I’m a developer and have been a full-time trader for the past few years.Recently I have been using LLMs more and more in my trading and strategy. I always found it frustrating that Claude Code or GPT did not have direct access to actual financial information and had to rely on web search, so it couldn’t get me more granular numbers for specific options…
Jul 2026 · finterm.ai
- 24
Ranked by how close each launch is in meaning, then by votes. Refine with a description →