Caddi vs. Harvey AIHarvey saves time while a lawyer uses it; Caddi runs the firm's operations with nobody at the keyboard.
Harvey is legal-grade AI for research and drafting. Caddi automates the back-office operations it doesn't touch, and delivers a reliable, deterministic win immediately while Harvey rolls out over months.
- 99%of agent runs complete successfully
- ~45 minon average to build your first agent
- 1M+back-office tasks completed
Jason AlafganiUpdated Sep 23, 2026
The back office isn't billable, but it still has to get done.
Intake, conflicts, billing, filing and inbox triage all land on operations, and none of it is legal research.
Legal-grade AI for research, drafting and document analysis, driven by attorneys.
Runs the operational work around the matter: intake, conflicts, billing checks, filing and inbox triage.
An assistant only works while someone is using it.
Three hundred client PDFs a day don't get renamed and filed into iManage or NetDocs because a lawyer has a great tool open.
Saves time while a lawyer uses it, with attorney review before the output is relied on.
Runs on its own whenever the work arrives, reading the documents and writing to your DMS and CRM the same way every time, with every step logged.
A firm-wide rollout takes months to prove out.
Procurement, security review and training come before the first result, and the budget for the next project often depends on that result.
Rolled out across the firm with the governance, training and partner support substantive legal AI needs.
Your ops team builds the first agent by describing the work in chat or on a screenshare. About 45 minutes on average to the first agent.
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 an agentic automation platform 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 immediately, 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's AI builds the automation from a recorded workflow, then production runs as deterministic code over APIs, with AI only on the steps that need judgment. 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?
Any model step can get something wrong, Caddi's included. What Caddi changes is how much of the run is left to chance. Non-determinism compounds: a step that is right 90% of the time comes out clean only 48% of the time across seven steps. Caddi runs the fixed steps as deterministic code, the same way every time, and keeps AI to the steps that need judgment, each one scoped, logged, and reviewable. Generative assistants like Harvey produce output on every step, which an attorney needs to review before relying on it.