Thinking

Exploration, not a service catalog

Ideas PromptFormr is actively exploring and experimenting with: how data systems are built, tested, and improved as AI becomes part of them.

Flagship theme

Closed-Loop Data Engineering

Systems that detect, evaluate, and improve data pipeline behavior through feedback loops: self-healing pipelines, automated regression detection, and agentic data engineering.

  • Self-healing pipelines
  • Regression detection
  • Continuous improvement
  • Agentic data engineering

Read the deep dive →

Exploration

LLMs as Data Transformation Engines

How language models become components inside data pipelines. They handle extraction, standardization, and mapping tasks that resist hand-written rules, and their outputs get validated like any other transformation.

  • LLM pipelines
  • Extraction
  • Standardization
  • Validated outputs

Exploration

Knowledge Graphs for Hidden Connections

How entity relationships reveal insights across financial and healthcare data, from AML risk networks to patient identity across fragmented clinical systems. We built a 2.3M-node knowledge graph from the ICIJ Offshore Leaks, OpenSanctions, and news extraction to trace sanctioned money through shell networks.

  • Entity relationships
  • Network analysis
  • Risk detection
  • Patient identity

Walk the graph →

Exploration

Multi-Agent Development Workflows

Leveraging AI coding with a continuously improving workflow. An agentic team of coding, review, and testing agents works inside the development loop: agents write the first draft, review each other's changes, and run the tests, and an engineer approves what ships. Each iteration feeds back into the workflow, so it gets better with use.

  • AI coding agents
  • Automated review
  • Agent-run testing
  • Repo management
  • Context management
  • Continuous improvement

Exploration

Reliable AI Systems

What it takes to run AI in production: evaluation frameworks, monitoring, testing, and workflows that catch model drift and regressions in the pipeline.

  • Evaluation
  • Monitoring
  • Testing
  • Production AI workflows

Builds Side projects

Working builds where these ideas get tested on real, messy, multi-source data.

Knowledge Graphs · GraphRAG

A knowledge graph to trace sanctioned money through shell networks

A 2.3M-node graph built from the ICIJ Offshore Leaks, OpenSanctions, and news extraction. Walk the traversal from a single UK Treasury fine to the shell-company network behind it.

sources → cleanse → graph db → traversal → context

Marketplace · OCR & Vision

CardTradr: OCR for card trading transactions

OCR and vision models parse photos of graded card slabs, classify each transaction (buy, sell, trade), and match it to grading data. Runs on cloud or local vision models.

Photos → parsing & matching → inventory and P&L dataset

Finance Ops · Billing Pipelines

Billing & invoice automation

Emailed receipts and invoices parsed into amounts, dates, vendors, and GL hints, plus automated monthly invoice generation from time-tracking data.

Email inbox → extraction → validated ledger entries

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These are active explorations. Conversations with practitioners make them better.

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