Alternatives
A CoCounsel alternative with the practice attached.
CoCounsel is a well-built AI assistant backed by a large research publisher. It answers questions and reviews documents. What it does not do is run your matters, capture your time, or bill your clients. ModulawAI does both halves in one system.
Side by side
Where the two differ.
| Capability | ModulawAI | AI assistant products |
|---|---|---|
| Research with citations | Yes, grounded in retrieved primary law | Yes, a core strength |
| Document review at volume | Tabular review: rows are documents, columns are questions, cells cite | Yes, typically conversational or per-task |
| Drafting in Microsoft Word | Native add-in with track-changes redlines and comments | Varies by product |
| Matters, deadlines, tasks | Full case management with audit trail | Not included |
| Time capture and billing | Multi-currency invoicing, retainers, trust reconciliation | Not included |
| Client portal and intake | Yes, enquiry through to signed retainer | Not included |
| Jurisdictions | US, UK, Canada, EU, Nigeria, Ghana, Kenya, South Africa | Primarily US and selected common-law markets |
Based on publicly available information at the time of writing. Verify current features and pricing with each vendor before deciding.
The real question
What happens to the output.
The gap
A brilliant answer in a window nobody bills.
A standalone assistant produces good work and then hands it to you as text. You copy it into a document, remember to record the time, and file it somewhere that the next person may or may not find. The three most valuable side effects of legal work, the billing record, the matter history, and the institutional memory, all depend on a human remembering to create them.
The alternative
The work lands where it belongs.
Because the AI runs inside the matter, the research attaches to the file, the time is captured against the client, and the authority is still there in eighteen months when the file is reassigned. That is not a smarter model. It is a better place to put one.
Shape of the product
Discrete skills versus a working surface.
Assistant products tend to be organised as a menu of discrete skills: summarise this, review that, prepare for a deposition. That is easy to demonstrate and genuinely useful. The limitation is that each skill starts from nothing. It does not know which matter you are on, who the client is, what was decided last month, or what the firm already holds on the same point.
Being fair
When an assistant is the better buy.
- You already pay a major research publisher. If an assistant is bundled with or discounted against a subscription you are keeping anyway, the marginal cost is low and that is a legitimate reason to stay.
- Your practice management is entrenched. A large firm mid-way through a different platform rollout should not start a second migration to get AI.
- You want one specific task done well. If the requirement is deposition preparation or a particular review workflow and nothing else, a focused tool is a reasonable fit.
- Your work is US-only. If nothing you touch crosses a border, multi-jurisdiction coverage is not worth paying for.
The case for ModulawAI is strongest in the opposite situation: a firm paying separately for practice management, research, and AI, copying between all three, and working on matters that do not stay inside one jurisdiction.
Running both
You do not have to choose immediately.
Plenty of firms run an assistant alongside ModulawAI during an evaluation, and some keep a specialist research subscription permanently for a niche practice area while moving day-to-day work across. ModulawAI exposes a scoped REST API and an MCP server, so it can be reached by other AI tools and by your own internal tooling rather than sitting behind a closed reporting screen. If you later decide to consolidate, matters, documents, time entries and invoices all export in standard formats.
One thing no research or drafting product does: build you a working tool
The automation story across this category is workflows. Harvey’s Agent Builder and Legora’s Workflows let a firm assemble multi-step processes in natural language, and Harvey reported more than 25,000 customer built workflows by February 2026 (harvey.ai). CoCounsel’s skills work on the same principle. All of them are pipelines: documents in, and documents, tables and answers out.
None of them produces a running application. ModulawAI includes Canvas, an interactive artifact builder that turns a plain description into working software. Describe a damages model, a client intake form, a limitation period checker, a settlement scenario board or a small internal dashboard, and you get a real page you can open and use, usually within minutes, with no code written by the lawyer. The closest equivalents are the general assistants rather than any legal product: Claude Artifacts and ChatGPT Canvas do this well, and neither knows your matters, your precedents or your jurisdiction.
Being fair about it cuts both ways. Canvas apps run in a sealed sandbox on an opaque origin with no network access, which is deliberate: the app cannot reach the matter file, firm data or any outside service, so you type its inputs in. They are internal tools today, and publishing one to a public address for clients is on the roadmap rather than in the product. What it buys a firm is a bespoke tool in an afternoon instead of a request that never reaches a development queue.
FAQ
Questions, addressed.
What is the best CoCounsel alternative?
For firms that want AI plus the system it should live in, ModulawAI is the closest alternative: research with linked citations, bulk document review, drafting inside Microsoft Word, and full practice management, billing, and client portals in the same platform. Firms that only want an assistant alongside existing systems may prefer a standalone product.
Does it replace our research subscription?
For many firms it does, since primary law across eight jurisdictions is included rather than sold separately. Firms with deep needs in a specialist area often keep a specialist database alongside it.
How does document review compare?
ModulawAI structures review as a grid rather than a conversation. Documents are rows, your questions are columns, and each cell carries a citation, which makes comparison across a set immediate and produces an exportable working document. See tabular review.
Can we run both during an evaluation?
Yes, and many firms do. ModulawAI also exposes a scoped REST API and an MCP server, so it can be reached by other AI tools and by your own internal tooling.
Is our data used for training?
No. Workspace data is segregated per firm, encrypted in transit and at rest, and never used to train third-party models.
How should we compare them properly?
Take a question you have already researched and a set of documents you already understand, run both, and open every citation. Feature tables do not settle this; verified output does.
See both halves working together.
Book a demo and we will run it on a real matter, from research through to the invoice. See all comparisons.