Managed legal AI priced per lawyer, or a platform the firm runs inside its own perimeter where privileged material never leaves
On ibl.ai you own all the code and the data, run it model-agnostic across any LLM, and pay with no per-seat pricing — so you can deploy anywhere, from your own cloud to a fully air-gapped network.
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Harvey is the best-known legal AI platform, built with large firms and tuned for the work they do — research, drafting, diligence, and transactional workflows that a general assistant handles poorly.
It is a managed service, and reported pricing sits in the hundreds of dollars per lawyer per month. Both facts matter to a firm: privileged material is processed on the vendor's infrastructure, and the cost scales with the size of the firm rather than the volume of work.
A firm-owned platform keeps matter material inside the firm's own network. There is no disclosure to a technology vendor to disclose to a client, no third-party retention question in an engagement letter, and no reliance on someone else's incident response for privileged content.
This page compares the two on the axes that actually decide legal AI: confidentiality, cost shape, and what the firm can still run when a contract ends.
by ibl.ai
Owned agentic AI platformby Harvey
Managed legal AI platform| Criteria | Self-Hosted AI | Harvey |
|---|---|---|
| Out-of-the-Box Readiness | Production agents for legal research, contract review, diligence, discovery support, and knowledge management once deployed, configured to how your organization actually works. | Immediately useful — deep legal workflow tooling built with large firms, covering research, drafting, diligence, and transactional work. |
| Integration With Your Systems | Deep integration with iManage, NetDocuments, Clio, Westlaw, and LexisNexis over APIs and MCP, running inside your own network. | Connects to common systems, bounded by the connectors the vendor has built. |
| Extensibility | Build and own workflows the vendor has not thought of, because you hold the code. | Configurable within the product; capabilities outside it require the vendor to build them. |
| Any-LLM & Model Control | Run any open or commercial model, route by cost, latency, and capability, and switch anytime. | Runs on frontier models Harvey selects and manages. |
| Criteria | Self-Hosted AI | Harvey |
|---|---|---|
| Self-Hosting / On-Prem / Air-Gapped | Runs on your servers, your private cloud, or fully air-gapped with zero external calls. | Runs in Harvey's cloud; it cannot be self-hosted or air-gapped. |
| Where the Data Lives | privileged client matters never leaves your environment, and every interaction is logged for audit. | Processed and retained on the vendor's infrastructure under your agreement. |
| Source Code Ownership | You hold the full source and can audit, fork, and extend every layer. | You rent access; the platform and its roadmap belong to the vendor. |
| Fit With attorney-client privilege and ABA ethics duties | Data stays inside your perimeter, which is the simplest posture to evidence under attorney-client privilege and ABA ethics duties. | Vendor compliance coverage under shared-responsibility terms. |
| Criteria | Self-Hosted AI | Harvey |
|---|---|---|
| Cost at Scale | Flat license plus compute you own — extending access across law firms and in-house legal teams does not multiply the bill. | per-lawyer licensing reported in the hundreds of dollars per user per month, so cost grows with the size of the organization rather than the work done. |
| Time-to-Value | Requires deployment and integration, or a partner who does both for you. | Usable almost immediately with no infrastructure work. |
| Support & Maintenance | Self-managed, or fully supported with forward-deployed engineers. | Fully managed by Harvey. |
| What You Keep If the Relationship Ends | A working platform and all your data, still running on your own infrastructure. | Whatever the contract allows you to export. |
When inference runs inside the firm's network, there is no transmission of privileged material to a technology vendor and nothing new to disclose to a client.
Harvey handles confidential material under enterprise terms, which is a normal vendor arrangement and satisfies many firms and their clients.
The question is what your most demanding clients require in their outside-counsel guidelines. An increasing number specify where their material may be processed.
A flat, self-hosted license means the cost of giving every fee earner and every paralegal access does not change with headcount.
Per-lawyer pricing is simple to model and, at reported rates, becomes one of the larger technology line items a firm carries once it is deployed broadly.
Firms routinely limit legal AI to a practice group because of the per-lawyer rate — which means the tool is rationed exactly where leverage would be highest.
A self-hosted platform runs air-gapped, so government, defense, and highly sensitive matters can use AI at all.
A cloud service cannot serve matters where the client or the classification forbids external processing.
For firms with government or national-security practices, this is not a preference — it is whether AI is usable on those matters.
Clients increasingly specify where their material may be processed, and self-hosting answers that requirement directly rather than through a vendor's terms.
Harvey's legal workflow depth is real and immediate, and for a focused practice group it needs no infrastructure work.
Per-lawyer pricing at reported rates makes firm-wide deployment the most expensive configuration, which is why it usually does not happen.
Air-gapped operation is the only way to use AI on matters where external processing is prohibited outright.
Timeline: Four to ten weeks depending on integration count and review requirements
Timeline: Days to a few weeks
ibl.ai is the agentic AI platform where you own all the code and the data. You self-host the entire stack inside your own perimeter, run it model-agnostic across any LLM and switch anytime, and pay by usage with no per-seat pricing — so you can deploy anywhere: your cloud, on-premise, GovCloud, or fully air-gapped.
ibl.ai runs inside the firm's own network, so privileged material is processed by a system the firm owns — with no transmission to a technology vendor and nothing new to disclose under an outside-counsel guideline. Agentic OS integrates with iManage, NetDocuments, Clio, Westlaw, and LexisNexis over APIs and MCP, applies guardrails and redaction before any model sees matter content, and logs every retrieval for conflicts and audit review. It runs fully air-gapped for government and classified matters. You own all the code and the data, run any model, and can deploy on any cloud, on-premise, or air-gapped — on a flat license rather than per lawyer.
Full source code under a perpetual license, running on your infrastructure. Not API access to someone else's platform — the stack itself is yours.
Run any LLM — Claude, GPT, Gemini, Llama, Command, or your own fine-tune — and switch providers without rewriting the platform.
Usage-based billing against a budget cap you set. Cost tracks what your organization actually uses, not how many people you employ.
Your cloud, your VPC, on-premise, GovCloud, or a fully air-gapped network with no outbound connectivity.
1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.
ibl.ai is family-owned and operated from New York, NY — a U.S.-headquartered, domestically-owned long-term partner, not a vendor that sells licenses and moves on.
See how ibl.ai deploys AI agents you own and control—on your infrastructure, integrated with your systems.