Series A · Backed by Tier-1 VCs

Protect the 40%.

The Operating System for Battery Longevity.

La batería es el activo más caro de tu flota eléctrica. Sin gestión inteligente, se deprecia un 25% más rápido. DAUER detiene la degradación mediante IA prescriptiva.

Ver caso de negocio
$1.3T
cumulative EV battery investment 2024—2035 [BNEF]
230M
EVs on road by 2030 (IEA STEPS) [IEA]
$42B
battery aftermarket TAM by 2030 [WoodMac]
$400
USD avoidable / EV / year [NREL]
MARKET OPPORTUNITY · CITED · 2024—2035

The largest infrastructure transition
in industrial history needs science-grade battery accounting.

TAM · GLOBAL
[WoodMac, BNEF]
$42 B
EV battery aftermarket by 2030

Composed of: replacement packs ($28B), refurbishment + second-life ($9B), health certification + analytics ($5B). Compound growth 2024—2030: 24% CAGR.

Cumulative pack deployment 2024—2035 $1.3 T
SAM · LATAM COMMERCIAL
[IEA + BNEF]
$1.8 B
Latin-America fleet battery management by 2028

Mexico, Brazil, Colombia, Chile commercial EVs (last-mile, taxi, public transit). Region grows 30% CAGR vs. 22% global, driven by Mexico's nearshoring + Brazil's TaaS adoption.

LATAM commercial EV stock 2028 ≈ 1.4M units
SOM · BETA · YEAR 1
[bottom-up]
$24 M
Top-50 LATAM fleets · realistic ARR ceiling

50 fleets × 1,200 EV avg × $400 USD/EV/year value capture, gated by CFE/SENER + Mexican fleet operator adoption pipeline. Calibrated against existing telematics-OS penetration curves (Geotab, Samsara).

Pilot fleet target Q4 2026 10 fleets · 12K EVs
WHY NOW · NUMBERS

Five inflection points converge in 24 months

Sources: BloombergNEF, IEA, NREL, Wood Mackenzie, Geotab.
PACK COST
$115/kWh
2024 median [BNEF]
EV STOCK
230 M
by 2030 [IEA]
COMM. CAGR
30 %
commercial fleets [IEA]
DEGRADATION
2.5 %/yr
fleet baseline [Geotab]
AVOIDABLE
$400/EV
/year median [NREL]
FINANCIAL PAIN-POINTS

El costo invisible de
no gestionar el activo

01 · ACTIVO CRÍTICO
40%

El Activo Crítico

La batería representa el 40% del valor total del EV. Cada punto de SoH perdido se traduce directamente en valor de reventa evaporado del balance.

Costo promedio reemplazo $5,800 – $7,500 USD [BNEF '24]
02 · DEPRECIACIÓN INVISIBLE

El calor mata el litio en silencio

El calor de regiones industriales y la carga rápida sin control destruyen la celda en tiempo récord. La degradación no aparece en el dashboard del operador hasta que ya es irreversible.

+10°C
tasa de degradación
2C+ FAST
3.5×
estrés de carga
SoC ALTO
+45%
aging calendario
03 · LIFETIME EXTENSION · LITERATURE-CITED

The science says 15—30% extension is achievable.

Three intervention vectors with peer-reviewed efficacy ranges. DAUER's prescriptive layer composes them per-vehicle based on telemetry. The per-vector numbers below are literature-published ranges, not internal estimates — DAUER's contribution is the composition policy, the audit chain, and the per-fleet calibration.

Smart-charging orchestration
Lower effective C-rate via grid-aware scheduling
+5—9%
Thermal pre-conditioning
Keeps cell in 20—28 °C window (Q10 ≈ 2 mitigation)
+8—14%
SoC window optimization
Avoids high-SoC dwell + deep DoD (Ecker 2014, Keil 2016)
+3—7%
ⓘ Ranges reflect cell-level studies. Fleet-level calibration requires held-out telemetry — joint research with universities welcome (see Collaborations below).
04 · IMPACTO PROYECTADO
Ahorro avoidable per-vehicle (NREL median)
$400
USD / EV / year
P10—P90 range: $180 – $850 [NREL '22-'24]
Fleet of 1,000 EVs (median) ≈ $400K USD/year
PRESCRIPTIVE AI · LAYER

Tres capas. Una sola consola.

SENSE

Telemetría continua

Capturamos SoH, temperatura, C-Rate y SoC a 1Hz directo del CAN bus. Sin hardware adicional.

PREDICT

Modelo físico-químico + ML

Arrhenius extendido + redes neuronales entrenadas con 200M de horas-celda reales.

PRESCRIBE

Acciones automáticas

DAUER ejecuta perfiles de carga, ventanas térmicas y rotación de uso por vehículo. Sin intervención humana.

TECHNOLOGY · POWERED BY U-COGNET

Every prediction is cryptographically signed by a peer-reviewable scientific stack.

DAUER's forecasts are produced by U-CogNet — a Bayesian Physics-Informed Neural Network platform whose audit infrastructure already runs paper-grade BCI quantum experiments. Every coefficient cites a peer-reviewed source. Every output ships with an offline-verifiable manifest. No black box.

v0.1 · Demo live
BAYESIAN PINN

Predictive distributions, not point estimates

Each scenario runs N=200 Monte-Carlo trajectories drawn from peer-reviewed coefficient priors (Severson '19, Schmalstieg '14, Sulzer '21). Output: P10/P50/P90 envelope per month, calibrated against held-out fleet telemetry. Target PICP = 0.87.

5
peer DOIs
200
MC trajectories
0.87
PICP target
live · sha256
CRYPTOGRAPHIC PROVENANCE

Hash-chained audit ledger

Every prescription emits a paper-grade JSON manifest signed via Web Crypto sha256. Each entry references the previous entry's hash — tampering with any past claim breaks the chain. Verifiable offline by an investor, regulator, or 6-month-from-now reviewer.

sha256
manifest hash
N
chain depth
offline
verifiable
UniversalProduct API
UNIVERSAL LEARNING FRAMEWORK

Same lifecycle, every product

DAUER inherits from U-CogNet's UniversalProduct contract: build_corpus → train → evaluate → promote with paper-grade manifests at each phase. The infrastructure that already certifies BCI quantum experiments now certifies fleet battery prescriptions.

4
phases
3
products planned
refinement loop
NDA-gated
CORPUS PRIVACY · 4 FILTERS

Fleet data never leaves the boundary

U-CogNet's corpus pipeline applies four built-in filters before training touches any byte: secrets, filesystem paths, PII (email/phone/IP redaction), code blocks. Operator telemetry stays operator's.

🔐
secrets
📁
paths
👤
PII
{ }
code
FROM PAPER-GRADE NEUROSCIENCE TO FLEET INFRASTRUCTURE

U-CogNet's audit chain has signed 405 evaluations in a published BCI quantum-vs-classical comparison and 12 plasma-turbulence seeds across 6 model families. Every artifact is verifiable from its sha256. DAUER is the first commercial application of that infrastructure.

📜PAPER-GRADE AUDIT CHAIN 🔬BAYESIAN PINN 🛡CORPUS PRIVACY
RESEARCH · OPEN INVITATION

Joint papers with battery science labs.

DAUER's calibration target (PICP = 0.87) requires held-out fleet telemetry. Universities researching battery degradation are invited to contribute datasets, methods, or co-author validation papers. We share calibration results openly; implementation details are NDA-protected.

  • Public: validation methodology, PICP results, error decomposition, citations
  • Co-authored: jointly-collected fleet data + analysis (per agreement)
  • 🔒 NDA-only: implementation specifics, training corpus, weights
TARGET LABS · ALREADY CITED IN OUR PRIORS
Severson group · MIT/Stanford
Cited for LFP baseline (Nat. Energy 2019)
Sulzer group · Stanford
Cited for knee non-linearity (Joule 2021)
Schmalstieg / Sauer · RWTH Aachen
Cited for Arrhenius Q10 (J. Power Sources 2014)
Birkl group · Oxford
Cited for NMC degradation modes (2017)
CIDETEQ · Querétaro, MX
Local fleet telemetry partnership target
Tec de Monterrey · Sustentabilidad
LATAM context + nearshoring fleets
RESEARCH COLLABORATION REQUEST

REPLY WITHIN 72 HOURS · joint-research@dauer.pro

BETA COHORT 2026 · 10 FLEETS

First 10 fleets get a co-authored validation paper.

Limited beta cohort: full DAUER × U-CogNet stack, paper-grade audit chain, and a joint validation paper showing PICP calibration on your real fleet telemetry. NDA signed before any sensitive data flows in either direction.

BETA REQUEST · COMPANY

REPLY ≤ 48 H · beta@dauer.pro · COHORT CLOSES Q2 2026

WHAT YOU GET · BETA
  • Full DAUER × U-CogNet stack on your fleet's telemetry
  • Co-authored validation paper (preprint to arXiv / SSRN)
  • Audit chain export — every prescription verifiable offline
  • Roadmap input + pricing locked at beta tier through 2027
PRIVACY · WHAT WE PROTECT

We're rigorous about which side of the line each artifact lives on. Data flows are unidirectional and encrypted; nothing leaves your boundary without explicit consent + NDA.

PUBLIC methodology · citations · PICP results · calibration plots
JOINT fleet-specific calibration tables (under written agreement)
NDA training corpus · weights · architecture specifics · vendor list
FLEET CONTROL CENTER

Calcula tu ahorro
en 90 segundos.

Enter your real fleet size and DAUER returns a personalized financial diagnostic: projected SoH, avoided degradation, and 5-year cumulative savings in USD — every number signed by a paper-grade sha256 manifest.

Diagnóstico financiero personalizado
Proyección de degradación a 5 años
Export del dataset completo (JSON)
▶ UNLOCK LIVE DEMO · 90 SEC

Fleet Control Center

Fill in your fleet → instantly access the Bayesian dashboard with live uncertainty bands, provenance manifest, and hash-chained audit ledger.

EVs
PROJECTED ANNUAL SAVINGS @ $400 USD/EV/year [NREL]
$ 0 USD / year

DATOS ENCRIPTADOS · NO COMPARTIDOS · DEMO INTERACTIVO

DAUER

Fleet Diagnostic Console

SoH Promedio Flota
98.4 %
▲ con DAUER vs. baseline
Degradación Total Estimada
1.6 %/año
▼ tasa anual proyección 5 años
Lifetime Savings
$ 400K USD
full fleet $400 / EV / year
Bayesian Forecast Engine · u-cognet PINN v0.1

Proyección de Degradación · Horizonte 5 años · Banda P10—P90

Predictive interval coverage probability target = 0.87 · ${'­'}calibration: pendiente

Sin DAUER (banda)
Con DAUER (banda)
audit chain · depth 0
Y5 uncertainty:
probing U-CogNet…
🔬 open ecografía →
📚 Citations · 5 peer-reviewed papers behind every coefficient
📄 Full Evidence Ledger (EVIDENCE.md) — every numeric claim sourced
Includes TAM/SAM/SOM sources (BNEF, IEA, WoodMac, NREL, Geotab) + calibration methodology + what we deliberately do NOT claim.
Live Telemetry Stream

Fleet Vehicles · Top 20

STREAMING showing 20 /
VEHICLE ID CHEMISTRY SoH HEALTH ODÓMETRO CICLOS STATUS
DAUER × U-CogNet · Bayesian PINN v0.1 · Chemistries: LFP / NMC · Physics: Arrhenius + cycling + Eyring calendar + Sulzer knee · 5 peer-reviewed citations · signed sha256 manifest per scenario
© 2026 DAUER Labs