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Agriculture AI agent · Herd production

Herd Production Management AI Agent

Run the breeding calendar, the ration record and the component and culling numbers behind them — the herd manager decides, and the veterinarian's prescription and feed directive stay untouched.

Typical delivery
4–6 weeks
Deployment
Your stack
Manager approval
Production only
After launch
Agent Care

What this agent does

Works the record, never the order

In

  1. 01

    A pregnancy check runs, and the agent posts the result against the cow, the service sire and the breeding date.

  2. 02

    A ration is mixed, and the agent reconciles the batch sheet against the ration the nutritionist approved.

Reason

  1. 03

    A sire list lands, and the agent screens both parents for the CDCB haplotype codes before a mating is proposed.

  2. 04

    A genetic report spans April 2025, and the agent re-expresses both sides on the base CDCB moved that month.

  3. 05

    A test day closes, and the agent trends components against the Net Merit weights as revised in 2025.

Decide

  1. 06

    An official SCC sample posts, and the agent counts how many of the last five sit above the PMO limit.

  2. 07

    A VFD is on file, and the agent tracks its expiry and the durations FDA's February 2026 guidance asks sponsors to add.

Out

  1. 08

    A cull list is drawn, and the agent reconciles genomic merit against the pregnancy inventory behind it.

  2. 09

    Execute write actions only inside the approval boundaries agreed during implementation.

Product statement

The agent models and schedules; the herd manager decides, and a veterinarian prescribes, signs the feed directive and diagnoses.

Example workflow

One breeding group, record to approval

  1. 1Herd record receivedParlour data, pregnancy check, test-day file or feed batch sheet
  2. 2Context assembledPregnancy inventory, the ration on file, component history and the prescribed protocol, each with its source
  3. 3Recommendation draftedBreeding list, ration note, component trend and confidence
  4. 4Controls appliedLabel-interval checks, haplotype screens, index-revision checks and confidence threshold

No human action required

Stages 1 to 4 run unaided, and nothing is bred, mixed or shipped at any of them — the agent is modelling, and the manager's lane opens at the confidence gate.

5DecisionBranches at the confidence threshold
High confidence

Goes to the herd manager to approve.

Low confidence

Adds a nutritionist or breeding-adviser read first.

Manager approval

The recommendation is held with its source records, its flags and the confidence.

Approve · Edit · Send to the adviser

Approved — released to the pen

  1. 6Herd software updatedOnly where write access and approval policy allow it
  2. 7Outcome evaluatedManager edits, conception outcomes, component movement and corrections after the group was bred

Edits

Every manager edit is counted in the evaluation.

What should not run autonomously

Human approval stays in control

Outside the boundary — human approval required

8 items

  • Designing or altering a synchronisation protocol.
    • Prescribing or ordering a reproductive hormone.
    • Issuing, extending or amending a feed directive.
    • Diagnosing mastitis or any other disease.

  • Automation boundary

    Agent acts unaided

    • ✓Build the breeding calendar and the eligible cow list for the herd manager.
    • ✓Track the ration on file against what was mixed.
    • ✓Trend components, cell counts and feed efficiency.
    • ✓Flag what the herd manager should weigh, and hold the decision for review.

    Any write happens inside the boundaries agreed at implementation, never ahead of approval.

    • Clearing milk or a cull cow after a withdrawal.
    • Approving the ration before it is fed.
    • Adding or changing a medicated article.
  • Changes to protocol, ration or approval rules.

Example output

One breeding recommendation, annotated

Everything the agent proposes is attached to the record it was drawn from.

Herd-production output · single animal

Illustrative example
Animal
Second-lactation cow
Recommendation
Eligible for the next timed-AI group on the protocol as it was prescribed
Days in milk
92 DIM
Source of record
Pregnancy check on file
Confidence
89%
Attribution
Herd manager and named veterinarian

As received

Taken from the pregnancy check and the breeding log — nothing on this side is written by the agent.

Source records used

  • Pregnancy-check result
  • Breeding and service log
  • Prescribed protocol

Why this animal

She is eligible on the protocol as prescribed — the call the manager makes.

What the score decides

Below the configured threshold the recommendation picks up a second read.

Action

ApproveEditSend to the adviser

Value

Where AI adds value

The same four claims, placed at the point in the workflow where each one applies.

Where the value lands

Value 01 – 04

Every animal

From the herd record

03Modelling

Model from the record

Draw on the herd records and the protocol, ration and index rules configured for the operation.

01Approved path

A protocol is a prescription

Routine breeding lists and ration checks arrive already worked.

02Human review

Send the manager to the decisions

Label conflicts, carrier matings and rising cell counts are marked and handed on — production is modelled here, disease is not.

04

Build an evidence trail

The decision, the record it was drawn from and the herd manager who approved it stay on the animal.

Integrations

Typical integrations

Five system groups connect to the same agent. Which of them are in scope is decided in discovery.

  • Herd management software

    • DairyComp 305
    • PCDART
    • BoviSync
    • Uniform-Agri

  • Milk testing & records

    • DHIA test-day files
    • Co-op bulk-tank results

  • Genetics & mating

    • CDCB evaluations
    • Bull stud mating files

Agent

Herd production management

  • Reads the records
  • Models the decision
  • Holds for approval

  • Feed & nutrition

    • TMR mixers
    • feed software
    • Ration formulation tools

  • Observability & evaluation

    • OpenTelemetry
    • Langfuse
    • Supported monitoring/evaluation sources

Integration availability depends on the client's existing systems and API access.

Agent controls

Six layers between the model and the pen

The controls nest, outermost to innermost. What none of the six holds is set out in the map below.

L6 · Outermost — last line of defence

Inward → L1 · closest to the model

L6Rollback / safe modePull the agent back to reporting-only when evaluation or production signals degrade.Roll back
L5Version monitoringTrack model, prompt, ration-rule and index-revision changes.Track
L4TraceabilityRecord the source records, the recommendation, the edits and the approval time.Record
L3Manager approvalHold recommendations for the named manager; it governs release, not whether the number underneath is right.Gate
L2Policy guardrailsTest recommendations against label intervals, ration rules and carrier screens; a failure returns them.Restrict
L1Confidence thresholdsRoute low-confidence recommendations to an adviser read before the manager sees them.Require review
Model coreRecommendation drafted — breeding list, ration note, component trend and confidence
L1 – L2
Test whether a recommendation may stand
L3
Puts the call in the manager's hands
L4 – L5
Keep the decision and the record behind it
L6
Falls back to production reporting when signals degrade

How Nestack evaluates it

Evaluate the production workflow — not only the finished recommendation.

Coverage runs the whole depth of the workflow, and every layer is cut by slice.

Surface — the decision the pen gets

  1. E1Final-output evaluationDid every number in the recommendation trace back to the record it came from?
  2. E2Step-level evaluationDid the agent use the right animals, the ration on file and the current index revision?
  3. E3Tool evaluationDid it read and write the correct animal and the correct field?
  4. E4Confidence calibrationDo low-confidence recommendations actually attract more manager edits?
  5. E5Slice evaluationHow does performance change across specific pen types?
  6. E6Business outcomeHow many recommendations needed a manager edit or a correction after the group was bred?

Floor — the outcome the operation answers for

Failure modes

Where each failure originates in the agent

Seven failure modes, placed at the stage each one originates.

Agent lifecycle

Direction of processing →

  1. 01 · Retrieval

    1 mode

    • HD-03

      Superseded index base

      Genetic trend read straight across the April 2025 base change.

    Stage gathers

    Herd records, ration on file, protocols and indexes

  2. 02 · Reasoning

    2 modes

    • HD-04

      Unlabelled interval

      An injection is shifted a day to suit the labour roster.

    • HD-06

      Stale component economics

      Protein is chased on pre-2025 cheque arithmetic.

    Stage proposes

    Breeding list, ration note, trend and confidence

  3. 03 · Tool / write

    2 modes

    • HD-02

      Carrier-by-carrier mating

      A haplotype column on the sire file is not parsed.

    • HD-05

      Medicated edit logged as feed

      An inclusion rate moves with no part 558 re-check.

    Stage writes

    Only where write access and approval policy allow it

  4. 04 · Output

    1 mode

    • HD-01

      Cell count read as disease

      A rising individual-cow count is routed as mastitis.

    Stage returns

    The decision the manager approves and the pen gets

  5. 05 · Change / Version

    1 mode

    • HD-07

      Silent index drift

      An index or ration-rule change widens what the agent will assert.

    Stage tracks

    Model, prompt, ration rules and index revision

  • Sev-1 · acts outside the prescribed label
  • Sev-2 · a wrong call reaches the pen
  • Sev-3 · records degrade, call goes to review
See the complete Agriculture failure-mode catalogue

Affected slices

A herd-level rate can hide one bad pen

A herd-level pregnancy rate can look acceptable while a few pen cohorts absorb most of the rework sitting behind it. Nestack reports the manager-edit rate by slice, not only in total.

Slice performance — reported separately, not only in aggregate

Illustrative example
SliceFailure rateLiftLift vs. thresholdStatus
First-lactation breeding groups5.7%3.8×Review
Fresh pens on a new ration3.1%2.1×Review
Purchased replacement heifers2.4%1.6×Watch
Established mid-lactation pens1.5%1.0×Normal

Bar: manager-edit-rate lift vs. the established-pen baseline · scale 0–4.0× · tick marks the 2.0× review threshold

2 of 4 slices over threshold

Evidence-linked improvement

Every cycle ends with a new case

A cycle is closed when the wrong breeding call is a case the next release must survive. That suite is what the next group bred is measured against.

Improvement cycle · five stages

Switchback — the path turns at Improve and returns at Learn

  1. 01

    Detect

    Manager-edit rate rises in a pen slice.

  2. 02

    Diagnose

    The heifer that was bred to the wrong bull is walked back through the sire file until the cause narrows to one.

  3. 03

    Improve

    The change leaves with a version on it and the groups that found it attached.

  4. 04

    Verify

    The release stays shut while any touched protocol case is still red.

  5. 05

    Learn

    It is held permanently, and the ration rules shift with it.

  6. Learn → Detect

    The return edge. The next group is worked against a suite one case longer.

Typical build scope

Twelve workstreams across six weeks

The build scope read against the delivery timeline. Week structure follows the six-week plan — discovery, sources, production workflow, evaluation, integration, then production validation and handover.

Workstream

Week 1Week 2Week 3Week 4Week 5Week 6

  1. 01Production-workflow discovery and decision boundary scoping.Week 1
  2. 02Herd, milk and genetics source assessment.Week 1, Week 2
  3. 03Protocol, ration and genetic-index rule mapping work.Week 1, Week 2
  4. 04Herd-record ingestion and normalisation.Week 2
  5. 05Modelling logic and record binding.Week 2, Week 3
  6. 06Confidence scoring and decision routing.Week 3
  7. 07Herd manager approval workflow.Week 3, Week 4
  8. 08Herd-software and feed-system integration.Week 5
  9. 09Breeding and ration cases.Week 4, Week 5
  10. 10Guardrails and approval controls.Week 4
  11. 11Animal-trail instrumentation.Week 5, Week 6
  12. 12Deployment, documentation and Agent Care handover.Week 6

12 workstreams · 6 weeks · bar shows the weeks a workstream is active — several run in parallel

Final scope and sequence confirmed in discovery

Engagement tiers

What each tier includes

Rows are the capabilities named in each tier's scope. Higher tiers include everything below them.

Capability✓ in scope · — not at this tierPilotOne site, one speciesProductionProduction herd systemsAdvancedMultiple sites / species
Introduced at Pilot
Modelling to your records and rules✓✓✓
Manager approval✓✓✓
Decision-accuracy baseline✓✓✓
Introduced at Production
Reporting by pen—✓✓
Approval workflow in your systems—✓✓
Approved write-back—✓✓
Herd-software integration—✓✓
Introduced at Advanced
Multi-site ration and label rules——✓
Multi-stage production approvals——✓
High animal count——✓
Multi-site production controls——✓
Build priceFrom $5,000From $8,000Custom quote
Final build price
Confirmed after discovery based on integrations, workflow complexity, herd size, approval controls and deployment requirements.
Separate from build
Build pricing is separate from recurring Agent Care, which covers managed monitoring, evaluations, incidents and verified improvements after launch.

What we need from you

What you bring, and what we build with it

Each input maps to a piece of build scope and a week in the delivery timeline.

  1. 01Your herd records and pen structure

    Herd-record ingestion and mapping

    Week 1

  2. 02Representative breeding and ration history

    Modelling baseline, rule extraction and record binding

    Week 2

  3. 03Your protocol, ration and index rule sources

    Protocol, ration and index rule mapping

    Week 1

  4. 04Access to relevant APIs, feeds or exports

    Herd, milk and genetics assessment, then integration setup

    Week 2

  5. 05Decisions you would not want acted on

    Protocol cases and failure-mode testing

    Week 4

  6. 06What no protocol change may skip

    Confidence scoring, decision routing, guardrails and approval controls

    Week 3

  7. 07Named herd managers to review recommendations

    Manager approval workflow, then pilot and production validation

    Weeks 5–6

Nothing else is required

Deployment, documentation and Agent Care handover are ours.

Delivery timeline

Four phases across six weeks

The phases are drawn to the weeks they occupy, and week 5 genuinely runs two things at once.

Phase

W1

W2

W3

W4

W5

W6

  1. DiscoveryW1
  2. BuildW2 – W3
  3. EvaluateW4 – W5
  4. Pilot & LaunchW5 – W6

Week focus

W1Production workflow discovery, rule mapping and the automation boundary

W2Herd, milk and genetics integration and the modelling baseline

W3Production workflow, confidence logic and manager-approval controls

W4Evaluation suite, label and carrier checks and failure-mode testing

W5Feed-system integration, pilot pens and targeted corrections

W6One breeding cycle run under the herd manager, then Agent Care handover

Reading the band
A bar covers the weeks its work is named in, and nothing else. The week 5 overlap is real, not padding.
At the end of W6
The last checks clear on live groups and Agent Care picks up monitoring.
Duration
Six-week plan shown · typical delivery 4–6 weeks depending on scope confirmed in discovery.

Next step · Agriculture AI agent

Build a herd production agent around your records and your advisers.

Show us your herd records, your ration on file and who signs off. Not another opinion on the protocol. A calendar built to the label your veterinarian prescribed, and a call that stays with your manager.

Typical delivery
4–6 weeks
Deployment
Your herd and milk records
Manager approval
Production only
After launch
Agent Care available

Nestack Agents · Herd production management

AGT-AGR-17 · Agent Care available after launch

Build a herd production agent

Four questions so the call starts from your actual setup — then pick a time that suits you.

About you
Your herd

No obligation. We’ll map the workflow, name the automation boundary and tell you if an agent is the wrong answer.