Merlin turns every milking event into a structured data record — cow-level measurements, milking by milking, building into longitudinal trend data that supports operational decisions across the dairy.
Six measurements. One spectral scan. Attributed to the individual cow, timestamped, and stored — building a longitudinal dataset that grows more useful with every milking.
Each milking generates a complete data record for the individual animal — component values, health indicators, and reproductive markers captured at the same instant, in the same scan.
Records accumulate into longitudinal profiles. Trends across milkings reveal patterns invisible in any single reading — drifts in component output, SCC trajectories, reproductive cycles.
Butterfat, protein, and lactose tracked at milking frequency against rolling baselines. Deviations flagged against the individual cow’s own history, not population averages.
Progesterone profiles build automatically across milkings — encoding luteal phase, estrus detection, and conception status without additional sampling or observation protocols.
Thresholds and trend rules generate alerts when individual cows deviate meaningfully from their own baselines. Early signal before clinical presentation. Targeted, not population-wide.
Data structured for integration with existing herd management systems, nutritionist workflows, veterinary records, and processor quality programs. Designed to fit existing tools, not replace them.
A single SCC reading is a data point. Continuous inline measurements create a timeline. Merlin structures milking-by-milking records into longitudinal visibility that supports earlier intervention, operational awareness, and more informed herd management decisions.
The platform surfaces the same underlying data differently depending on who is looking at it — and what decision they need to make.
Component averages, health alerts, and reproductive status available daily rather than monthly. The platform supports operational decisions without adding labour or changing existing routines.
SCC and lactose trending at milking frequency provides a diagnostic window ahead of clinical signs. Progesterone profiles make reproductive disorders visible without additional sampling or scheduling.
Butterfat, protein, and MUN at milking frequency give nutritionists a near-real-time window into how cows are converting feed. Ration adjustments validated in days rather than at the next DHIA cycle.
Processors gain component visibility at farm level before pickup. Research partners access high-frequency phenotypic datasets — individual cow records at milking frequency — that periodic testing cannot produce.
Operational philosophy
Milk the cow.
Milk the data.
Every milking event already generates the raw material for operational intelligence. Component composition, udder health status, reproductive cycle, nutritional efficiency — all encoded in the biochemical signature of the milk itself. The platform is the infrastructure to read that signal, structure it, and make it useful. Continuously. For every cow.
Periodic testing creates an information structure that is inherently reactive. By the time a problem appears in a monthly bulk tank result, the underlying condition has been developing for weeks. Intervention at that point addresses a consequence, not a cause.
Continuous inline data changes that structure. Problems surface as trends before they become events. Decisions can be made closer to the moment the data was generated. Management can be anticipatory rather than corrective.
This is not a claim about guaranteed outcomes. It is a description of the information environment that continuous measurement creates — and the decisions that environment makes possible.
The data pipeline runs automatically. No sample handling. No laboratory wait. No change to existing milking routine.
Milk passes through the Merlin sensor during a standard milking event. Near-infrared spectroscopy captures the molecular signature of the milk. Six parameters derived from one scan.
Measurements are calibrated, processed, and attributed to the individual animal. Each milking event generates a complete structured record — timestamped and linked to the cow’s longitudinal history.
Records accumulate into trend data. Threshold rules and pattern detection surface alerts when individual cows deviate from their own baselines — early signal, not isolated data points.
Structured insights delivered to the right role — producer, nutritionist, veterinarian, or processor — in the format they need to act. Data designed to integrate with existing workflows.
We’re working with a focused group of producers, processors, veterinarians, and researchers ahead of commercial launch. If continuous inline milk intelligence sounds relevant to your operation, we’d like to hear from you.