Systems online — Bangalore, India

Intelligent
Systems,
Built from the
Ground Up.

End-to-end embedded AI for industrial automation. Sensor to insight — every layer owned, every protocol spoken.

See the Stack Talk to Us
ModBus BACnet Zigbee BLE MQTT CAN Bus RS-485
Signal flow // Talon Stack LIVE
Data rate 10kHz
Active protocol ModBus
Edge latency <12ms
// Live System

The stack, in motion.

Click any node to explore. Pulses show real data flow — sensor to insight, every layer owned.

Sensor layer
Multi-axis vibration, temperature, pressure, and current sensors. Industrial-grade, 4–20mA and digital interfaces. Data acquisition at up to 10kHz sampling rate.
10kHz
Sample rate
// 01 — The Stack

Every layer. One team.

Most vendors own one piece of the chain. We own all of it — which means no integration gaps, no data loss, no finger-pointing between vendors.

01
Sensors
Vibration, temperature, current, pressure. Multi-axis, industrial-grade.
4–20mA RS-485 I²C
›
02
Edge
On-device inference. Real-time anomaly detection before the cloud.
ARM Cortex RTOS TFLite
›
03
Gateway
Protocol translation. Bridging legacy and modern systems seamlessly.
ModBus BACnet Zigbee BLE
›
04
Cloud
Scalable ingestion, storage, and processing of high-frequency telemetry.
MQTT REST TimeSeries
›
05
Analytics
AI-driven insight. Predictive alerts, health scoring, plain-English reports.
Anomaly AI RUL Dashboard
// 02 — Domains

Deep in three verticals.

Not general-purpose IoT. Specific, hard-won expertise in the systems that matter.

DOMAIN / 01
Drive Controls
Motor fault detection before failure. Vibration signature analysis at the edge. Predictive maintenance for VFDs, servo drives, and industrial motors.
Unplanned downtime reduction Early bearing fault detection Energy efficiency monitoring
DOMAIN / 02
Automotive BMS
State-of-health estimation for EV battery packs. Cell-level balancing analytics, RUL prediction, and warranty intelligence for OEMs and fleet operators.
SoH and RUL estimation Cell-level anomaly detection Thermal runaway early warning
DOMAIN / 03
Green Energy & Solar
String-level performance monitoring for solar installations. Inverter health, yield vs. expected analysis, and grid-scale BESS degradation tracking.
Per-string yield analysis Inverter fault prediction BESS degradation modeling
// 03 — Approach

How we work.

Industrial systems are hard. We've been inside them. Here's our process — no ambiguity.

01 / ASSESS
System audit
We map your existing hardware, protocols, and data flows. Most sites have more signal than they realize — and more gaps than they expect.
02 / INTEGRATE
Sensor & gateway deploy
Hardware installation, protocol configuration, and edge device setup. We handle the physical layer so your team doesn't have to.
03 / CONNECT
Cloud & analytics
Data pipeline to our cloud platform. AI models trained on your specific equipment — not generic benchmarks.
04 / MONITOR
Live intelligence
Real-time dashboard, automated reports, anomaly alerts. Your team sees plain-English insights, not raw telemetry.
// 04 — Why Talon Tech

The gap we close.

Most companies need an embedded vendor and an AI vendor. We're both — and that changes what's possible.

Full protocol fluency
From legacy ModBus on a 20-year-old PLC to modern MQTT over cellular — we speak all of it natively. No middleware, no translation layer, no vendor lock-in.
ModBus / BACnet / Zigbee / BLE / CAN / MQTT / RS-485
Intelligence at the edge
Anomaly detection that runs on the device, not in the cloud. Sub-100ms response. Works on intermittent connectivity. No data leaves the site unless it should.
ARM Cortex-M4 · TFLite Micro · RTOS
End-to-end ownership
One team owns sensor through dashboard. When something breaks, there's no vendor chain to chase. We know exactly where the problem is because we built all of it.
Hardware · Firmware · Gateway · Cloud · Analytics
AI trained on real signals
Our models are trained on actual industrial equipment behavior — not academic datasets. Embedding-based anomaly detection that learns what your machine's normal looks like.
Time-series embeddings · Unsupervised anomaly · Domain-specific models
Edge inference — ARM Cortex-M4, <12ms latency Protocol stack — 7 industrial standards, no middleware Anomaly detection — unsupervised, no labeled data required MQTT broker — 10k msg/sec sustained throughput Battery SoH — ±2% estimation accuracy on LFP and NMC Solar monitoring — per-string, weather-adjusted yield analysis OTA updates — secure firmware delta, <30s downtime Edge inference — ARM Cortex-M4, <12ms latency Protocol stack — 7 industrial standards, no middleware Anomaly detection — unsupervised, no labeled data required MQTT broker — 10k msg/sec sustained throughput Battery SoH — ±2% estimation accuracy on LFP and NMC Solar monitoring — per-string, weather-adjusted yield analysis OTA updates — secure firmware delta, <30s downtime
// 05 — Contact

Start a conversation.

We work best with teams that have a real problem — a machine that fails unexpectedly, a sensor network that doesn't talk to anything, or data that just sits unread. Tell us what you're dealing with.

Bangalore, Karnataka, India