You’re automating processes
you’ve never measured.
Ledgerium captures the real process first — so your agents execute accurately, not aspirationally.
The problem
The automation blind spot
Automating the unknown
Teams deploy RPA and AI agents into processes described in workshops, not observed in reality. The documentation is a best-guess reconstruction — not a record of what actually happens.
Hallucinated workflows
AI agents built on assumed step sequences break when the real process has 3x more steps and undocumented workarounds. Your agent is executing confidently against fiction.
No baseline, no measurement
Without observing the current process, you can't measure if automation actually improved anything. You shipped the agent — but you have no idea if it's faster, more accurate, or just differently broken.
How it works
Observe. Blueprint. Measure.
Observe before you automate
Record the actual human workflow. See every step, timing, system context, and decision point before handing it to an AI agent. Ground your automation in evidence, not assumptions.
Generate automation blueprints
Structured process data with step sequences, system interactions, and timing — ready to feed into n8n, Zapier, or custom agent frameworks. Give your agents a map of reality, not a sketch from memory.
Measure the delta
Re-record after automation. Compare human vs. automated execution step by step. Quantify what improved and what regressed — so you ship with evidence, not hope.
What you get
Everything your agents need to execute correctly
Process capture with full context
Every step recorded with system state, navigation path, and decision context
Step-by-step execution sequences
Ordered, structured event chains ready for agent consumption
System interaction mapping
Which tools, fields, and UI surfaces the process touches — and in what order
Timing and duration baselines
Per-step and end-to-end timing so you can measure automation against reality
Confidence scores per step
Signal quality indicators that surface ambiguous steps before they become agent failures
Automation opportunity scoring
Identify which steps are high-value automation targets and which require human judgment
Capture the real process
before you automate it
Give your AI agents ground truth, not workshop notes. Record actual human execution, generate structured blueprints, and measure the delta after automation ships.