Measured data turns safe transport into a premium.
A logistics AI standard that normalizes the measured data Carbon DTG reads directly from the vehicle, to power the shift to safe transport. Through a single API and MCP it does more than safety — it also runs carbon-data analysis and LCS API functions: an AX product that stands one tier above LCS.
One tier above LCS.
Through API and MCP, LAS runs not only safety but also carbon-data analysis and LCS API functions in one place. It includes everything LCS does, and adds safety and conversational AI on top.
LAS runs them as-is — carbon-data analysis and LCS API functions.
On the same measured data, it adds safe-driving and operation analysis.
Carbon and safety together through one API·MCP — an AX product one tier above LCS.
Measure it, and it becomes a premium.
Measurement opens two premium shifts — carbon (LCS) into green transport, safety (LAS) into safe transport. Both are proven by data, so both return as pricing.
Measured carbon data lowers your shippers’ Scope 3 and connects verified green transport to premium orders.
Measured safety data proves safe operation and connects it to premium hazmat and high-value freight.
Both shifts are proven by sealed measured data, not claims — so they return as your wins, pricing, and reduced risk.
Proof coordinates — the green premium on lcs_record_hash, the safety premium on score_hash. Both are sha256 deterministic seals, so you bring reproducible data to the pricing table, not a claim.
Safety, handled as data.
Automated safe-driving score
Normalizes driving, hard accel/braking, idling and more that Carbon DTG measures, into an automatic safety score.
Safe-operation analysis
Analyzes risk patterns by vehicle, driving, and route to identify where and which vehicles need safe transport.
Safe-vehicle dispatch support
Helps prioritize verified-safe vehicles for hazmat, explosives, semiconductors and other loads that require safe transport.
Routes that lower the accident rate
Proposes routes that avoid black-ice risk zones and accident-prone segments — reducing the chance of an accident itself.
Conversational AI · Q&A
Grounded in normalized safety data, teams ask in natural language and get answers with their evidence.
Carbon analysis · LCS API, unified
On the same surface it also runs carbon-data analysis and LCS API functions — safety and carbon through one API·MCP.
The score comes from signals the vehicle actually made.
Safe-driving scores aren't invented. Carbon DTG already reads risk-driving signals; we normalize them per 100 km and compute them with a version-pinned deterministic function. Rules make the number, not the AI — the AI only does data processing and cited Q&A.
Each score is sealed as an sha256 of its input vector (score_hash) — reproducible and verifiable, the same way carbon emissions are sealed. No data (DTG unlinked) shows as "not measured", never zero (n/a ≠ 0). Hazmat dispatch safely excludes vehicles without a score.
AI does the method; data does the verdict.
LAS’s AI doesn’t invent numbers. It generates and answers only through a normalized data-processing methodology, while safety scores and verdicts are computed deterministically. Every output carries its source.
- Uses only normalized measured data — no fabricated estimates
- Numbers and verdicts are deterministic · AI assists method and narrative
- Every AI output shows its provenance · n/a ≠ 0
- Evidence is sealed measurement — data, not claims
Build easily, with Claude Code.
Experiment in the playground, integrate via the API, and build straight from Claude Code with LAS MCP (agent-to-agent).
A space to experiment with safety and carbon analysis conversationally.
Beyond safety scores and analysis, wire in carbon analysis and LCS API functions as one.
Agent-to-agent protocol for Claude Code developers.
LAS MCP includes LCS MCP as-is (all carbon tools) and adds safety and conversational tools on top. Scores and verdicts are deterministic (score_hash sealed); matching is a recommendation, not auto-dispatch. (In development)