Acquire
Receive heterogeneous OBD-II CSV logs without assuming one vehicle, logger, or sampling interval.
Prototype platform · Vehicle intelligence
Intelligence for
every machine.
AIAM converts heterogeneous machine telemetry into canonical evidence, reconstructed journeys, durable machine memory, and operator-ready intelligence.
CANONICAL MODEL37 CONCEPTS
PILOT FLEET3 MACHINES
INGESTIONVALIDATED
The intelligence pipeline
From raw signal to defensible machine intelligence.
One governed path transforms vehicle-specific logs into a stable, reusable machine record.
Route
Identify the source schema and direct every field through the appropriate machine translation profile.
Canonicalize
Map source-specific fields into the stable AIAM canonical vocabulary defined by AIAM-CS-1.0.
Validate
Preserve provenance, verify time integrity, and reject evidence that cannot be defended.
Interpret
Reconstruct the journey and produce machine memory, evidence packets, and intelligence outputs.
Machine registry
A platform proven across different machines.
AIAM learns the source without forcing every machine to speak the same native language.
MACHINE 001ACTIVE PILOT
2015
BMW 535i
- SYSTEM
- N55 / OBD-II
- ROLE
- Primary telemetry baseline
MACHINE 002VALIDATED
2020
GMC Yukon Denali
- SYSTEM
- GM ENHANCED PIDS
- ROLE
- Cross-platform validation
MACHINE 003INGESTED
2015
Ford Mustang GT
- SYSTEM
- OBD-II / MODIFIED
- ROLE
- Compatibility validation
Intelligence outputs
The machine does not need another dashboard. It needs memory.
Every validated session becomes part of a durable evidence system designed to grow more valuable over time.
Journey Reconstruction
Recreate what the machine experienced across time using defensible source evidence and valid geography.
Machine Memory
Build a durable operating history that compounds in value every time the machine is observed.
Evidence Packets
Preserve normalized telemetry, provenance, validation results, and conformance decisions together.
Intelligence Reports
Translate raw signals into concise findings about operation, health, efficiency, and cost.
Proprietary foundation
A governed architecture between raw machine data and human decisions.
AIAM separates acquisition, translation, canonicalization, validation, and interpretation so each layer can evolve without corrupting the evidence beneath it.
- 01 Source-aware ingestion
- 02 Canonical signal governance
- 03 Evidence-grade provenance
- 04 Machine-specific memory
04INTELLIGENCE EXPERIENCEReplay · Reports · Cost · Health
03MACHINE MEMORYJourneys · Baselines · Evidence
02MAE + AIAM-CS-1.0Route · Map · Normalize · Govern
01AIAM-INGEST-0.1.1CSV · OBD-II · Adaptive Timeline
Founder-led prototype
Give the machine a memory.
AIAM is validating the first vehicle intelligence pipeline before expanding to fleets, equipment, agriculture, industrial systems, marine, and energy.
Request pilot access mike@aiaugmentedmachines.com