EARNED AI // v2.0
Spec sheet ↓ Launch demo →
ANSI/EIA‑748 · DOE 413.3B · DCMA 14‑PT

Earned value,
measured/audited/narrated

A project‑controls intelligence platform that ingests Primavera P6 schedules, recomputes EVM from first principles, quantifies risk with real Monte Carlo, and writes the monthly report for you — with every formula, float, and variance open to inspection.

Built from scratch CPM engine Monte Carlo DCMA 14‑Point XER parser Claude‑generated narratives
Open live demo ↗ Read the spec sheet
Instrument · Project selector
K‑GSF
Yucca‑II
Hanford WTP
BAC
$2.40M
CPI
0.94
SPI
0.87
% Complete
62.4
PV (plan) EV (earned) AC (actual) TODAY · DATA DATE
01 — WHAT IT DOES

Oversight, in three registers.

Mirrors DOE PMSO workflow
from CD‑0 to close‑out
I.
Cost / EVM oversight

Validate the contractor's numbers.

  • CPI/SPI trended against baseline
  • Cost‑at‑completion breach alerts
  • EAC comparison across three methods
  • TCPI feasibility, flagged automatically
II.
Schedule surveillance

Prove the schedule is real.

  • DCMA 14‑Point health assessment
  • Critical‑path integrity checks
  • Float anomalies & constraint abuse
  • Earned Schedule: SPI(t), SV(t)
III.
Risk & reporting

From probability to prose.

  • Monte Carlo cost & schedule bands
  • AI anomaly detection with severity
  • Portfolio roll‑up and drill‑down
  • Narrative reports generated via Claude
02 — CORE ENGINES

Six engines, hand‑rolled.

Tap a row to expand
capabilities
All
Cost
Schedule
Risk
AI
Integrations
6 engines · 32 capabilities · 0 dependencies on commercial EVM libraries
03 — APPLICATION SURFACE

Nine screens, one story.

Scroll horizontally
or use arrows →
Swipe for all nine
04 — WHY IT'S BUILT THIS WAY

Every line is defensible.

No black‑box calcs
No vendored formulas

DCMA 14‑Point, implemented in full.

Composite quality score · 86 / 100 · 12 pass · 2 fail
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