The best eDiscovery software tools available today combine AI-powered document review, production automation, and transparent pricing. DecoverAI ranks as the most AI-native option — processing documents from upload to court-ready production in under an hour at $60/GB flat rate with no seat fees.
We evaluated eight leading eDiscovery platforms across six criteria most relevant to legal teams: what each platform is best suited for, its AI capability, pricing model, whether it charges seat fees, and how long it takes to get a new matter up and running.
| Platform | Best For | AI Capability | Pricing Model | Seat Fees | Setup Time |
|---|---|---|---|---|---|
| DecoverAIAI‑Native | AI-native review & production | Generative AI (LLM-based) | $60/GB flat rate | No | Minutes |
| Relativity | Large enterprises | TAR / CAL predictive coding | Per-user license | Yes | Weeks |
| Everlaw | Mid-to-large firms | ML-assisted review | Per-GB + users | Yes | Days |
| CS Disco | Enterprise litigation | AI-assisted search & tagging | Per-GB + users | Yes | Days |
| Logikcull | Small-to-mid firms | Basic AI / keyword | Per-doc + storage | Yes | Days |
| Casepoint | Government & enterprise | AI-assisted review | Custom pricing | Yes | Weeks |
| Nuix | High-volume processing | Processing only | Per-case | Varies | Weeks |
| Reveal | All firm sizes | AI review | Per-GB | Partial | Days |
Pricing note: Pricing models change frequently. Relativity, Everlaw, CS Disco, and Casepoint all offer custom enterprise contracts that may not reflect published rates. DecoverAI's $60/GB all-inclusive rate includes processing, hosting, AI review, privilege log generation, and production — with no seat fees, overage charges, or module fees.
The most important distinction in eDiscovery software today is not which platform has the most features — it is whether the platform was built with AI at its core or had AI bolted on as an afterthought.
Relativity was founded in 2001 and Logikcull in 2004 — decades before large language models existed. Their AI features (TAR, CAL, predictive coding) are statistical models trained on reviewer decisions, grafted onto document management workflows that were never designed for AI-first processing. Adding AI is a continuous retrofit, not the original architecture.
DecoverAI was designed from the ground up with large language models as the engine for every step: document classification, privilege analysis, confidentiality detection, production setup, and privilege log generation. There is no separate AI module — the entire platform is the AI system, which allows it to operate as an integrated pipeline rather than a series of disconnected tools.
On a traditional platform, a team might spend two to three weeks processing, reviewing, and producing a large document set. On an AI-native platform, the same matter can be completed in hours. The cost difference is proportional: fewer reviewer hours, faster production timelines, and predictable per-GB pricing rather than unpredictable per-seat, per-module, and per-hour billing.
Not every eDiscovery platform will fit every legal team. These are the five criteria that matter most when evaluating your options.