How Machine Learning Transforms and Automates Legal Services, by Arnoud Engelfriet, Co-Founder at Lynn Legal. *Machine Learning School in The Netherlands 2022.

1. How Machine Learning
transforms legal services.
Arnoud Engelfriet, co-founder and partner Lynn Legal bv

2. Hi Arnoud,
Can you review this NDA? I’m about to have a meeting, so want to sign quickly.
Hello Arnoud,
Just checking, is this NDA ok to sign? Showstoppers only, we’re already in discussions
with these guys.
Hi Arnoud,
Can I sign this NDA?? Please let me know urgently
Hi Arnoud,
Just wanted to confirm this NDA is no problem, I already signed it 

8. About Lynn Legal
We are lawyers who understand technology. More than
anyone else, we know how to build software that adds
value to practically all legal processes.
• Creates practical legal solutions
• By people who have a strong background in both the
technical and legal field
• Years of experience in legal consultancy
• Operating in various sectors of industry, including
government, healthcare and legal

9. How does Lynn work?
1. Submit your document in Word, PDF, RTF or
plain text (web, API or e-mail)
2. Automated screening, response within
approximately 2 minutes
3. Trained on thousands of source documents,
labeled by experienced domain expert lawyers
4. Checked on more than 40 issues, from
applicable law to penalty provisions, security
requirements, audits, etc.
5. Specific advice for your position
6. Download annotated Word document

10. Automated document review in 5 steps
1 •Text extraction
2 •Clause identification
3 •Clause flavoring
4 •Report compilation
5 •Amending document

11. Quick poll!
What is your company’s position on …
a) Maximum liability in your service contracts?
b) Contractual penalties in NDAs?
c) Audit rights to your data processors?
d) Longest acceptable payment term in a
customer’s purchasing terms?

12. The power of the playbook
A legal playbook codifies the business
requirements and limits for contract review.
Often these are in the lawyer’s head(s).
Deploying legal tech forces you to make
the rules explicit.

13. Playbook per use case

14. Pre-check: Give users a
feeling of what the human
lawyer will say
Pre-check: Give users a
feeling of what the human
lawyer will say
Quickscan: If lawyerbot says
OK, it’s ok
Otherwise send it to the
human lawyer
Quickscan: If lawyerbot says
OK, it’s ok
Otherwise send it to the
human lawyer
Fast lane: If value is low
then let lawyerbot review it
Otherwise send it to the
human lawyer
Fast lane: If value is low
then let lawyerbot review it
Otherwise send it to the
human lawyer
Preliminary scan: First
resolve the issues raised by
the lawyerbot. Then send it
to the human lawyer.
Preliminary scan: First
resolve the issues raised by
the lawyerbot. Then send it
to the human lawyer.

15. • Change: high
• Risk reduction: high
• Cost savings: medium
• Change: high
• Risk reduction: high
• Cost savings: high
• Change: low
• Risk reduction: medium
• Cost savings: medium
• Change: minimal
• Risk reduction: low
• Cost savings: low
Precheck
Precheck Quickscan
Quickscan
Preliminary
scan
Preliminary
scan
Fast lane
Fast lane

16. Monthly cost
Monthly time spent
0
2000
4000
6000
8000
10000
12000
14000
Manual Lynn
0
10
20
30
40
50
60
70
Manual Lynn
Cost and time savings

17. Thank you!
A.Engelfriet@lynnlegal.ai
Linkedin: Arnoud Engelfriet
Lynn Legal B.V.
Jollemanhof 8a
1019 GW Amsterdam
+31 20 229 33 45
info@lynnlegal.ai
juriblox.nl
lynnlegal.ai