Caddi and Harvey aren't really competitors. Most firms run both. Harvey is a generative AI assistant for substantive legal work. Caddi automates the back office, intake, conflicts, billing, filing, and inbox triage, all running unattended as deterministic code. The question isn't which one; it's what to roll out first.
The basics
What is Harvey?
An AI assistant for lawyers that helps with research, drafting, and document analysis.
What is Caddi?
The deterministic AI automation platform for ops and admin teams. Ops teams teach Caddi their workflows over a screen share, and then Caddi runs them reliably hundreds of times a week.
Get the quick win first, then layer in legal AI
Our Legal AI Adoption Framework makes the case plainly: legal-specific platforms tend to be reliable but slow to roll out, so the first move should be a workflow that is both reliable in production and fast to deploy. Caddi is that first move, Wave 1 revenue operations and Wave 2 firm operations, while Harvey lands later as the firm builds the governance, training, and partner support that substantive legal AI requires.
Why deterministic wins for operational work
For the high-volume, repetitive back-office work that drives capacity, three things matter most, and they're exactly where deterministic automation beats a pure-AI approach.
Cost
Generative legal AI runs large language models on every task, so cost scales with model usage and per-seat licensing. Caddi uses AI only at setup to understand a recorded workflow; production then runs as deterministic code, so the per-run cost is low and predictable even at high volume.
Reliability
Once an automation is built, Caddi runs it the same way every time, a repeatable, auditable process that doesn't hallucinate. Generative output is probabilistic and needs a human to review it before it's relied on, which is the right model for legal drafting but the wrong one for unattended operational throughput.
Speed
Agentic AI reasons step by step in sequence, fast for a single draft, slow as a production pipeline. Deterministic code executes immediately over APIs, so Caddi clears intake, filing, and inbox work at a pace a chained-LLM workflow can't match.
Caddi vs. Harvey at a glance
| Harvey AI | Caddi | |
|---|---|---|
| What it is | Generative legal AI assistant | Done-for-you back-office automation |
| Primary user | Attorneys (substantive work) | Ops & admin teams (operational work) |
| Human in the loop | Yes, attorney reviews output | No, runs unattended |
| Production runtime | LLM generation each time | Deterministic code; AI only at setup |
| Reliability | Probabilistic; needs review | Repeatable; doesn't hallucinate |
| Cost model | Per-seat + model usage | Low, predictable per-run |
| Time to value | Months (rollout, governance) | Days (record once) |
| Best fit | Legal operations (Wave 3) | Revenue + firm ops (Waves 1–2) |
How they score where it counts
Harvey is the clear leader for substantive legal research and drafting. Caddi leads on the things that make operational automation pay off quickly, cost, reliability, speed, and time-to-ROI.
What using each one feels like
The day-to-day models are different: Harvey is a tool an attorney drives; Caddi is a workflow that runs itself. Toggle between the two.
- 1Record the operational taskA non-technical teammate screen-shares an intake, filing, or inbox workflow.
- 2Caddi writes deterministic codeAI understands the task at setup; production runs predictably over APIs.
- 3It runs unattendedPDFs are filed, inboxes triaged, and records updated across 70+ tools.
- 4Caddi maintains itUpkeep and edge cases are handled for you, no model to babysit.
Which fits your need
Which fits your situation?
Harvey AI
Substantive, attorney-facing legal work is exactly what Harvey is built for.
Frequently asked questions
Is Caddi an alternative to Harvey AI?
Not exactly, they work at different layers, and most firms run both. Harvey is a legal AI assistant for substantive work like research, drafting, and document analysis that an attorney reviews. Caddi is done-for-you automation for back-office operations: intake, conflicts, billing, filing, inbox triage, and PDF-to-system-of-record work that runs unattended as deterministic code. Caddi handles the operational work Harvey isn't built to do.
Should a law firm choose Caddi or Harvey?
It's usually not either/or. The fastest path is to sequence them: start with Caddi for revenue and firm operations because it's reliable, deterministic, cheap to run, and live in days, then roll out Harvey in parallel for substantive legal work over the following months as governance and training mature. The quick, measurable Caddi win earns the budget and credibility for the larger Harvey rollout.
Why is Caddi cheaper to run than legal AI like Harvey?
Harvey generates output with large language models on every task, so cost scales with model usage and seats. Caddi uses AI only at setup to understand a recorded workflow, then runs production as deterministic code over APIs. Because production runs don't call an expensive model for every step, the per-run cost is low and predictable.
Does Caddi hallucinate the way generative AI can?
No. Once an automation is built, Caddi runs it as deterministic code, so the same inputs produce the same outputs every time, a repeatable, auditable process rather than a fresh generation. Generative assistants like Harvey produce probabilistic output that an attorney needs to review before relying on it.
Start with the quick win
Bring an operational workflow that's eating your team's time. Caddi will build it from a screen recording and run it across 70+ tools. See real examples, read the Legal AI Adoption Framework, or book a demo.
Do more with less
See Caddi in action
Tell us where to reach you and the calendar opens right here. In 30 minutes we'll show you how Caddi automates the back-office work that grows with your clients—built, run, and maintained for you.