Use case 1
Client intake agent
Qualifies leads, captures matter details, schedules consults, and routes by practice area.
For managing partners, firm owners, legal ops leads
03
AI workflows for SMB law firms: intake, matters, billing, and follow-up.
Cut repetitive document and admin work out of your firm while attorneys keep doing the judgment work clients pay for.
01
The work that is quietly eating margin.
Run the firm. Let agents handle the paperwork.
1Intake leads slip through the cracks
2Paralegals are buried in document review
3Billing narratives are written from memory
4Client follow-up depends on who remembers
5Matter knowledge lives in one attorney inbox
02
The closed-loop system OpenNash builds.
Same operating pattern, tuned to SMB Law workflows.
01 Intake
Capture
Read work from the tools your team already uses.
02 Reason
Decide
Classify, retrieve context, choose the workflow, and flag risk.
03 Draft
Produce
Create the response, report, memo, update, or work product.
04 Approve
Control
Route judgment-heavy or sensitive actions through human review.
05 Learn
Improve
Measure outcomes, exceptions, quality, and cycle time.
Feedback loop: every completed workflow becomes a signal for the next version.
03
High-leverage use cases.
Start where the volume, pain, and business value overlap.
Use case 2
Matter summary agent
Generates running summaries from emails, filings, documents, and notes.
Use case 3
Document classification
Sorts production sets, contracts, and discovery materials with human-confirmed labels.
Use case 4
Transcript digest
Turns depositions and transcripts into searchable summaries with pinpoint references.
Use case 5
Billing narrative drafter
Drafts compliant time entries from calendar, email, and document activity for attorney review.
Use case 6
Client follow-up automation
Tracks every open client commitment and sends the right nudge at the right time.
Note: OpenNash systems support attorney judgment. They do not replace it. Every output should be reviewed before it leaves the firm.
04
Before and after.
Representative outcomes depend on scope, data quality, systems, and volume.
Before
Manual drag
- Intake leaks at the front door
- Billable hours lost to admin
- Realization rate creeping down
- Knowledge dies when partners retire
to
After
AI-enabled ops
- Every intake captured and routed
- Admin compressed by 60%+
- Cleaner narratives, higher realization
- Firm knowledge stays in the firm
Intake conversion
+25%
Representative range
Admin hours per matter
-45%
Representative range
Billing realization
+5-10 pts
Representative range
Cycle to invoice
-7 days
Representative range
Next step
Automate your firm's repetitive legal ops.
Book a 30-minute meeting or email [email protected] with the workflow that hurts, the tools involved, and what success would look like in 90 days.