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Shepherd Review 2026

Vet-founded, AI-powered practice software with flat unlimited-user pricing

8.2/10

ReviewLake Score

Best for: Small animal general practices wanting a modern, intuitive platform with flat, predictable pricing

Our quick verdict

Buy it if

Small animal general practices wanting a modern, intuitive platform with flat, predictable pricing.

Think twice if

Newer platform with a shorter track record than legacy systems like Cornerstone

Biggest strength: Flat unlimited-user pricing makes budgeting simple compared to per-user models

Biggest weakness: Less deep integration with the broader Covetrus ecosystem than Covetrus Pulse

At a glance

Best for

Small animal general practices wanting a modern, intuitive platform with flat, predictable pricing

Pricing model

Published pricing

Typical team size

1-20 people

ReviewLake Score

8.2/10

Last reviewed 2026-08-01.

Pricing

Pricing model

Published

Flat, published pricing around $299/month per doctor with unlimited users - easier to budget than per-user competitors

See Shepherd pricing

Score breakdown

8.2/10
Ease of use
8.5
Features & depth
8.3
Value for money
8.0
Customer support
8.0
Small-business fit
8.3

Based on our independent research, not vendor-reported or user-submitted data. See ourmethodology.

Pros & Cons

What we like

  • Flat unlimited-user pricing makes budgeting simple compared to per-user models
  • Built-in AI features (TranscribeAI, DiagnoseAI) and interactive body maps for modern documentation
  • Founded by veterinarians, reflected in workflow design that user reviews consistently rate highly (4.7-4.9 stars)

What to watch

  • Newer platform with a shorter track record than legacy systems like Cornerstone
  • Less deep integration with the broader Covetrus ecosystem than Covetrus Pulse
  • AI features are relatively new - worth testing directly against your specific clinical workflows

Who is Shepherd for?

Ideal for

  • Small animal general practices wanting a modern, intuitive platform with flat, predictable pricing
  • Teams of 1-20 people

Not ideal for

  • Newer platform with a shorter track record than legacy systems like Cornerstone
  • Less deep integration with the broader Covetrus ecosystem than Covetrus Pulse
  • AI features are relatively new - worth testing directly against your specific clinical workflows

Shepherd stands out for two genuine reasons: it was built by veterinarians rather than a general software company, and it prices flat per doctor with unlimited users rather than charging per seat. That combination shows up in consistently high user review scores and a workflow that reportedly fits how small animal general practices actually operate day to day, including an escalating automated recall sequence (email, then text, then postcard) that logs client responses directly into the patient file.

Looking for a different fit? These are the closest comparisons in our own research.

EezyVet logoezyVet
8.0/10

Cloud-based practice management with deep IDEXX diagnostic integration

Full ezyVet review →
VSVetspire logoVetspire
7.8/10

Cloud-based veterinary platform with AI-assisted charting

Full Vetspire review →
CCornerstone logoCornerstone
7.7/10

Established on-premise practice management for large, established hospitals

Full Cornerstone review →

Frequently asked questions

How much does Shepherd cost?

Flat, published pricing around $299/month per doctor with unlimited users - easier to budget than per-user competitors. Confirm current rates directly with Shepherd, since published pricing can change.

Is Shepherd good for small businesses?

Yes - Shepherd's own small-business fit score is 8.3/10, one of its stronger dimensions.

Who is Shepherd best suited for?

Small animal general practices wanting a modern, intuitive platform with flat, predictable pricing.

How we scored this

This score is based on our own independent research across five weighted dimensions - ease of use, features & depth, value for money, customer support, and small-business fit - not vendor-reported or user-submitted data. Last reviewed 2026-08-01.

Read our full methodology →
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