Network Engagement Analysis
Lily Clifford
Lily Clifford
CEO & Founder, Rime Labs
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Who’s engaging with
Lily Clifford

126 founders, AI engineers, and operators engaged with Lily Clifford’s feed across 9 posts in the last three weeks — the people drawn to Rime’s voice-AI research and its rapid hiring, with names, titles, companies, and engagement depth.

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Data collected October 2, 2026 · 126 engagers from 9 posts · 3-week window (Sep 11 – Oct 2, 2026)
👥
📊
📝
⚡
Engagers
126
Posts
9
Reactions
161
TOP ENGAGERS
HAHarsh Agarwal
Harsh Agarwal
RHRobert Haley
Robert Haley
JVJohn Vrionis
John Vrionis
CL
Calvin Ling
HW
Hongchen Wu
0
Unique Engagers
0
Posts Analyzed
0
Reactions Captured
The Network

126 people who showed up

Real names. Real titles. Click any card to open their LinkedIn profile. Search by name, title, or company — filter by reaction type. This is the audience a voice-AI founder attracts in public: AI/ML engineers, founders and VCs, and the GTM operators building at AI companies.

🔍
126 people match
The Inner Circle

27 people engage with Lily’s posts again and again

These engagers showed up across 2+ posts in the window — a three-week snapshot along a founding team’s hiring run. They’re not casual scrollers: they’re the builders, investors, and operators tracking Rime closely, with 12 of them at 3+ posts. Highest-trust relationships in the dataset.

Most consistent engagers — ranked by posts engaged
HAHarsh Agarwal
Harsh Agarwal
Ex-Founder | Product Manager · 4 posts
RHRobert Haley
Robert Haley
Stripe · GTM @ Stripe | ex-Scale AI | 2x Fulbright Alum · 4 posts
JVJohn Vrionis
John Vrionis
Lecture Faculty Stanford · Unusual Ventures, Lecture Faculty Stanford · 4 posts
CL
Calvin Ling
Unusual Ventures · VP of Finance at Unusual Ventures · 3 posts
JP
Jeff Pulver
Founder, The vCon Foundation | HD Voice for Voice AI | Voice and Conversations on the Net · Atlanta · Oct 13–15 · 3 posts
LMLaura Montenegro
Laura Montenegro
Cognitive Linguist | Conversation Designer | Sociolinguist · 3 posts
HFHermes Frangoudis
Hermes Frangoudis
Agora · Helping developers build the future of Voice-first conversational AI apps. Dev Experience @ Agora · 3 posts
JVJon Volk
Jon Volk
Unusual Ventures · Operating Partner @ Unusual Ventures | Talent Acquisition · 3 posts
BT
Brett Teele
Unusual Ventures · Chief Financial Officer and Partner at Unusual Ventures · 3 posts
NCNidal Cheema
Nidal Cheema
Datum Labs · Principal Data Engineer @Datum Labs | Leading Vero, Data Infrastructure for Growing Teams | Dagster, dlt, dbt, BigQuery, Snowflake, Hex, Kubernetes · 3 posts
GAGuilherme Antônio Silva, M.Sc
Guilherme Antônio Silva, M.Sc
Technical Program Manager | Conversational AI • LLMs • NLP • Voice AI | PSM I | MBA USP/ESALQ | Former Apple & Google · 3 posts
MIMustak I.
Mustak I.
CSR · Co-Founder @ CSR | We help early-stage VC-backed startups build the teams that get them to the next round | NYC · 3 posts
HW
Hongchen Wu
Georgia Institute · Associate Professor at Georgia Institute of Technology · 2 posts
AB
Aleks Bass
Typeform · CPTO at Typeform | Writing about research-driven product strategy, AI transformation, and decision quality. · 2 posts
IDInaan Damaraju
Inaan Damaraju
Confido Health · Forward Deployed Eng @ Confido Health | prev @ Lindy ai | MS + BS @ USC | Stay Curious! · 2 posts
KNKshitij Nakhashi
Kshitij Nakhashi
Datasetsmith.com · Founder @ Datasetsmith.com - Speech, Healthcare & Autonomous Driving Data | Data Scientist | 360° Marketing Communication Specialist · 2 posts
WAWallysson Abreu
Wallysson Abreu
Data Annotator | Medical Interpreter | Language Specialist · 2 posts
DRDoug Regner
Doug Regner
Helping technical founders go from $0-$1m · 2 posts
Where They Work

The employers that do show up

42% of Lily’s engagers carry an employer in their headline. The pattern flips between AI builders and investors: funds like Unusual Ventures sit next to the AI labs and startups — the two audiences that orbit a voice-AI founder’s feed.

🏢
Top companies by engager count
Unusual Ventures ↗
3 engagers · 3 senior · 3 repeat
Google ↗
2 engagers · 1 senior
Krassowski & Co ↗
2 engagers · 2 senior
Stripe ↗
1 engager · 1 repeat
Lecture Faculty Stanford ↗
1 engager · 1 repeat
Georgia Institute ↗
1 engager · 1 repeat
Agora ↗
1 engager · 1 repeat
Datum Labs ↗
1 engager · 1 senior · 1 repeat
The absence of corporate clusters IS the insight: Lily’s network is AI builders plus the capital and operators around them — the exact market for voice-AI infrastructure, tooling, and talent.
Senior Signals

The named employers with senior voices

When a founder, partner, or senior operator from a named company engages Lily’s feed, that’s an account-level signal worth knowing — even when it’s one person. Ranked by seniority, repeat engagement, and engager count.

🎯
Ranked by senior-signal score
Unusual Ventures ↗3 engagers · 3 senior · 3 repeat
Calvin Ling, Jon Volk, Brett Teele
Krassowski & Co ↗2 engagers · 2 senior · 0 repeat
Tom Krassowski, David Krassowski
Datum Labs ↗1 engager · 1 senior · 1 repeat
Nidal Cheema
Csr ↗1 engager · 1 senior · 1 repeat
Mustak I.
Datasetsmith.Com ↗1 engager · 1 senior · 1 repeat
Kshitij Nakhashi
Asurion ↗1 engager · 1 senior · 1 repeat
Ofer Beit Halachmi
Google ↗2 engagers · 1 senior · 0 repeat
Krista Campbell
Totalenergies ↗1 engager · 1 senior · 0 repeat
Lazzat K
Most engagers here are founders or engineers whose “company” is a lab, a fund, or their own venture. The named employers below are the ones worth tracking as investors, partners, or hires.
Content Appetite

Industry POV vs. team & hiring news

Does Lily’s audience show up for her voice-AI research and industry takes, or for the company-news drumbeat — hiring and team welcomes? The two pull different crowds — here’s who shows up for each.

🔗
Who engages with what
134
POV / research only — 38 (28%)
Team / hiring only — 78 (58%)
Both — 18 (14%)

3 of 9 posts are industry POV or research; 6 are hiring and team news. The single research post on flawed TTS benchmarks reached the most technical slice of the audience — while the hiring posts drove the broadest reach, led by “The Rime team has grown a lot over the last 6 months, but I haven't po…” (88 likes).

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Likes per post, by type

Blue = industry POV / research · Purple = team & hiring news. POV posts pulled 110 likes across 3 posts; team/hiring posts pulled 228 across 6.

88
09-11
C
16
09-14
C
25
09-16
C
18
09-22
E
21
09-22
C
25
09-24
C
36
09-29
E
56
09-30
E
53
10-02
C
Network Composition

Who is this network — and does it fit your ICP?

Rime Labs builds human-quality voice models; Lily leads it in public from San Francisco. Her feed pulls the exact crowd that follows voice AI closely — AI/ML engineers and researchers, founders and early-stage investors, and the GTM operators selling AI into enterprises. Here’s how her 126 engagers break down.

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Seniority Breakdown
Operator / Independent
65%
Founder / CEO
18%
C-Suite / GP
9%
VP / Director
8%
🏭
Role Focus
Founders & Executives
27%
AI/ML Engineering
25%
GTM & Sales
17%
Research & Academia
8%
Product & Design
3%
Finance & Capital Markets
2%
IT & Infrastructure
2%
Executives & Leaders
1%
Other
16%
🏢
Where They Work
Unusual Ventures
100
Google
67
Krassowski & Co
67
Stripe
33
Lecture Faculty Stanford
33
Georgia Institute
33

42% of engagers list an employer in their headline — a mix of AI labs, funds, and the engagers’ own ventures.

Engagement Depth

How the network engages

Reaction mix tells you the *type* of attention Lily’s content gets; the repeat rate tells you who’s actually paying attention vs. passively scrolling. A founder’s hiring and research posts pull congratulation-heavy reactions — and the same names keep coming back.

👍
LIKE
140
87.0% of reactions
👏
PRAISE
12
7.5% of reactions
❤
EMPATHY
8
5.0% of reactions
💡
INTEREST
1
0.6% of reactions
Engagement pattern — depth of relationship
Single post
79%
2–3 posts
19%
4+ posts
2%
What Drew Them In

The content that built this network

9 posts on Lily Clifford’s feed analyzed (Sep 11 – Oct 2, 2026). This is a founding team scaling in public — hiring posts and team welcomes set the cadence, while the research post on why TTS benchmarks are flawed pulled the most technically senior audience of the window.

1
“The Rime team has grown a lot over the last 6 months, but I haven't posted about every role. Here's one that's…”
2026-09-11
88 likes · 11 comments · 1 shares
88
likes
2
“Public benchmarks of TTS are fundamentally flawed. We'll spend 99% of our time building better models, but we …”
2026-09-30
56 likes · 3 comments · 5 shares
56
likes
3
“Rime is hiring! We’re looking for new folks to join the team across go-to-market and machine learning. If you’…”
2026-10-02
53 likes · 4 comments · 7 shares
53
likes
4
“I'm really excited about this one. We’re talking voice AI - beyond the hype. We’re going to be talking about w…”
2026-09-29
36 likes · 0 comments · 1 shares
36
likes
5
“Welcome, Augusto Alvarez! Excited to have you here at Rime.…”
2026-09-24
25 likes · 0 comments · 0 shares
25
likes
6
“Welcome to Rime, Gabe!…”
2026-09-16
25 likes · 1 comments · 0 shares
25
likes
7
“Excited to have Moy Yuan on the team!…”
2026-09-22
21 likes · 1 comments · 0 shares
21
likes
8
“This is going to be a good one! If you'll be in SF for tech week, make sure you RSVP for this panel.…”
2026-09-22
18 likes · 0 comments · 0 shares
18
likes
9
“Welcome, Dima!…”
2026-09-14
16 likes · 0 comments · 0 shares
16
likes
What This Data Tells You

Four angles worth acting on

This isn’t a list of likes. It’s a map of the voice-AI ecosystem forming in public around a founding team that’s hiring fast — and most of it isn’t being worked.

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A founder’s feed is a live ICP roster
126 verified engagers · 161 reactions captured · 9 posts in three weeks — and 338 likes, 20 comments, 14 shares across the feed. The comment volume on hiring posts (avg 2 per post) shows a network that actually replies and referrals, not just reacts.
🎯
84% of engagers match an AI-economy profile
106 of 126 people are founders/execs, AI/ML engineers, research, or GTM operators — the exact audience for voice-AI infrastructure, developer tooling, and enterprise AI sales. For anyone selling into that market — or recruiting in it — this feed is a weekly meeting with the ICP.
🎖
Founders and decision-makers are in the room
44 senior engagers — 23 founders/CEOs, 11 C-suite/GPs, 10 VPs/Directors. The most consistent include Harsh Agarwal (4 posts), Robert Haley (4 posts) — repeat engagers across a three-week hiring run.
🔁
27 people never miss a post
27 people engage 2+ times and 12 engage 3+ times in three weeks. On a nine-post feed, that repeat rate is relationship formation, not traffic — these are the people watching Rime’s build-out in real time.

The question isn’t whether people engage with Lily’s content. It’s who’s engaging that nobody’s working.

So What

What you’d actually do with this

Data is only as good as the decision it changes. Here’s the same analysis, read two ways.

🧭
If you sell to the AI economy

This is a live map of buyers for voice-AI infrastructure, developer tooling, and enterprise AI: 126 named people, including 23 founders/CEOs and 31 AI/ML engineers and researchers — the builders who spec and buy this market. Every one of them is a warm signal — and most aren’t in any CRM.

Unusual Ventures leads the senior-signal ranking — 3 engagers, 3 senior. When a firm’s people track a founder this consistently, that’s an account with a paper trail.

👥
If you’re hiring, partnering with — or studying — Rime

Her feed is a public roster of the voice-AI talent market: 31 AI/ML engineers and researchers, 23 founders, and a long tail of GTM operators who engage every hiring post. For a team scaling this fast, the engagement is a referral pipeline.

27 people engage with 2+ posts in three weeks — a loyal core that no algorithm change can take away. The relationship layer already exists; the missing piece is a system that turns public engagement into routed pipeline.

Who’s engaging with your posts that you’re missing opportunities with?

kokasexton.com turns any LinkedIn profile’s engagement into a ranked, filterable map of the people who actually show up — with names, titles, companies, seniority, and one-click LinkedIn links. The data is already in your feed. This is what it looks like analyzed.

Get Your Own Network Analysis → View Lily Clifford on LinkedIn ↗