Customer Story
How a global agricultural equipment maker runs the telemetry from 1,000+ sensors per combine on Akka — turning raw machine data into real-time field decisions.
John Deere built its Precision Ag service on Akka to collect and analyze the data from 1,000+ sensors on every combine, fused with weather feeds and seed and fertilizer manufacturer data. Raw machine telemetry became real-time guidance that raises crop yields, lowers production costs, and increases equipment margins for the farmers who buy its machines.
Akka ROI Scorecard
Time to stand up the Precision Ag data pipeline. New sensor models and analytics ship continuously rather than on a multi-month release cycle.
Infrastructure cost to ingest and analyze fleet telemetry. The same growing sensor volume runs on a fraction of the compute.
sensor events per second ingested across the connected fleet, correlated in real time with weather and agronomy data.
Business outcome: more efficient crop yields, lower production costs, and higher equipment margins.
John Deere sells large industrial equipment, and each combine now carries 1,000+ sensors that capture data on every operational aspect of the machine — hydration levels, fertilizer and pesticide application by crop type, and how efficiently crews operate expensive, complex equipment. The value to the farmer is not the raw data. It is the return on a multi-hundred-thousand-dollar machine, and that return depends on turning sensor readings into decisions during the narrow windows when a field can be worked.
The volume was the obstacle. A single machine generates a continuous stream of telemetry, a fleet generates orders of magnitude more, and the data is only useful when it is correlated in real time with weather and with seed and fertilizer manufacturer data. John Deere needed to collect and analyze that stream at fleet scale without the cost and operational overhead growing in step with the sensor count.
John Deere built its Precision Ag offering on Akka to collect and analyze the sensor data at scale. The platform ingests high-volume telemetry from combines and tractors, joins it with weather feeds and manufacturer data, and returns analysis fast enough to guide equipment use in the field. The same workload runs on a fraction of the infrastructure a conventional data pipeline would require, and the services stay responsive as fleet volume grows.
Agents connect to GitHub, Prometheus, Datadog, and New Relic, ingesting telemetry at minute-level granularity tuned to each source's rate limits. Akka coordinates event-based agent workflows, with built-in guardrails and checkpoints that prevent runaway token usage or infinite analysis loops. The result is elastic data ingestion feeding a live entity-relationship graph, resilient concurrency that keeps telemetry pipelines stable under pressure, and clean, maintainable ingest code that a 10-person team can operate at enterprise scale.
This is the Never Fail guarantee: Akka handles clustering, resilience, durable in-memory state, and traffic steering, so the application does not have to.
Scale. John Deere ingests and analyzes telemetry from the full connected fleet — 1,000+ sensors per combine, correlated in real time with weather and agronomy data. The platform absorbs peak-season load, when every machine in a region is in the field at once, without a separate workaround pipeline.
Real-time healthcare. Health professionals can instantly and securely discuss patients' cases and protocols with colleagues and peers through rich media messaging or voice and video calling without interrupting time-sensitive workflows.
Security and compliance. This solution maintains the highest of global standards and complies with the GDPR, E-Privacy, the NHS information governance, DCB 0129, ICO, ISO 27001, and NEN 7510, 7512, and 7513.
Cost to operate. The infrastructure cost to run the Precision Ag pipeline is significantly lower than a conventional stack for the same telemetry volume, so cost does not grow in step with the number of connected machines and sensors.
Speed to production. Build effort dropped significantly. New sensor types and analytics models move into production continuously rather than on a multi-month cycle.
Business impact. Precision Ag became a distinct service offering that delivers more efficient crop yields, lower production costs, and higher margins to farmers — driving greater customer satisfaction, loyalty, and follow-on equipment sales for John Deere.
The Precision Ag data pipeline is the foundation for a field agent. On the Akka Agentic AI Platform, an AI agent ingests the live telemetry from a combine's 1,000+ sensors, fuses it with weather and seed and fertilizer manufacturer data, predicts crop yield and impending equipment failure, and recommends field actions — hydration, fertilizer and pesticide timing, and routing — while the machine is still working the field. Every recommendation runs on durable state that survives failure, with sub-minute recovery, at the same fleet scale John Deere already ingests today.
The platform that scaled John Deere's sensor analytics is the same platform that builds and runs agentic AI today. Enterprises build on the Akka Agentic AI Platform directly, or have a system delivered and operated through Akka Specify. Both provide the production guarantees John Deere has run on for years.
