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Process-First Consulting

Keep it Simple
Analytics

Understand your process. Prototype the solution. Keep it simple.

AI consulting and workflow optimization for small businesses — we fix the process before picking the tools. Process mapping, rapid prototyping, and AI automation delivered in weeks, not months.

What We Do

Process first. Tools second.

⚙️

Process Engineering

Business process improvement starts with understanding what you have. We do process mapping, identify bottlenecks, and design workflows that actually work — so you stop paying for software that collects dust.

Rapid Prototyping

Prototype development from concept to working proof-of-concept in weeks, not months. Validate ideas with real data before committing to full builds. Fail fast, learn faster.

🤖

Agentic Engineering

AI automation for small business — we design and build autonomous agents that research, analyze, and execute under human oversight. Local-first, no vendor lock-in.

Proof of Capability

Built to solve real problems

A sample of proof-of-concepts from our portfolio — rapid prototypes that went from idea to working system.

17.5B rowsrecords analyzed

Healthcare Price Transparency at Scale

Visualized 17.5 billion negotiated rate records across 20K+ billing codes and 10K+ providers. Interactive analytics with sub-50ms query latency.

ClickHouseD3.jsReact
7 agentsautonomous pipeline

Healthcare Data Pipeline

End-to-end Transparency in Coverage pipeline: provider registry, TOC parsing, MRF rate extraction, and normalization. 7 specialized AI agents orchestrating the flow.

LangGraphFastAPIDuckDB
Fully autonomousresearch pipeline

Deep Research Agent

Autonomous research system: iterative web search, content extraction, vector embeddings, hybrid retrieval, and citation-gated report synthesis.

FastAPISearXNGpgvector

Rapid Prototyping in Practice

How we built Parq-Bench

A real example of our process — from identifying a pain point to shipping an open source tool.

The Problem

Analysts were stuck. Excel crashes on large files. Pandas needs a Python environment. Spark needs a cluster. There was no simple way to just look at big data.

Our Approach

We mapped the workflow, identified the real bottleneck (getting eyes on data fast), and prototyped a local-first desktop tool — no cloud, no setup, no dependencies.

The Result

5GB files open in under 500ms. 46.7 million rows rendered at 60 FPS. Full-table SQL aggregation in 641ms. Shipped as a single binary.

Want us to build something like this for your business? Let's talk.

Ready to simplify?

Tell us about your process challenge. We'll show you what's possible.