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Mar 24, 2017 · 23m · mad

Leveraging AI in the Enterprise // Kuang Chen, Captricity (FirstMark's Data Driven)

Kuang Chen · 19m spoken Matt Turck · 1m spoken
0:00 / 0:00
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions

At a DataDrivenNYC event hosted by FirstMark Capital, Captricity CEO Kuang Chen outlines how legacy enterprises can overcome structural data limitations by unlocking unstructured dark data through cloud-based, high-accuracy AI infrastructure to drive operational efficiency and customer satisfaction.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 6.6% of the talking time here. How this is scored →

Matt as informed peer 1.0 Guest teaching 1.3 Guest disagreement 0.7 Matt pushing back 0.9
05100:0010:0020:000:53–4:34 · Matt as informed peer 0/10 State of the Enterprise and Rising Business Uncertainty This segment is a presentation monologue by Kuang Chen introducing the macro challenges facing enterprises. The host does not participate, requiring zero host-side scores.4:34–6:48 · Matt as informed peer 0/10 Case Study on Netflix Data Transformation and AI Strategy Chen delivers a solo presentation detailing Netflix's evolution from DVD mailing to data-driven content creation. As a pure monologue segment, host metrics remain zero.6:48–9:11 · Matt as informed peer 0/10 Key Solution Criteria for Successful Enterprise AI Chen presents solution criteria for enterprise AI, focusing on first-party dark data and high accuracy thresholds. The host remains silent throughout.9:11–13:58 · Matt as informed peer 0/10 Captricity Enterprise AI Infrastructure Architecture Chen explains Captricity's architectural layout and human-in-the-loop dynamic training system. The host does not join the discussion.13:58–16:17 · Matt as informed peer 0/10 Unlocking First-Party Dark Data and Medical Insights Chen uses case studies on death certificates and East African vaccination registries to illustrate dark data normalization. The host is non-participatory.16:17–19:39 · Matt as informed peer 3/10 Strategic Enterprise Benefits of Normalized Data Matt Turck steps in at the end of the presentation to ask about the human and social engineering aspects of enterprise AI sales. Chen agrees and expands on buyer skepticism, resulting in a cooperative interaction.19:39–23:53 · Matt as informed peer 4/10 Q&A on Cloud Security and Machine Intelligence Architecture Turck asserts that enterprise deployments must be on-premise, but Chen corrects him by stating Captricity is 100% cloud-based. Turck adapts and pivots to ask about Fortune 1000 cloud security concerns.0:53–4:34 · Guest teaching 0/10 State of the Enterprise and Rising Business Uncertainty This segment is a presentation monologue by Kuang Chen introducing the macro challenges facing enterprises. The host does not participate, requiring zero host-side scores.4:34–6:48 · Guest teaching 0/10 Case Study on Netflix Data Transformation and AI Strategy Chen delivers a solo presentation detailing Netflix's evolution from DVD mailing to data-driven content creation. As a pure monologue segment, host metrics remain zero.6:48–9:11 · Guest teaching 0/10 Key Solution Criteria for Successful Enterprise AI Chen presents solution criteria for enterprise AI, focusing on first-party dark data and high accuracy thresholds. The host remains silent throughout.9:11–13:58 · Guest teaching 0/10 Captricity Enterprise AI Infrastructure Architecture Chen explains Captricity's architectural layout and human-in-the-loop dynamic training system. The host does not join the discussion.13:58–16:17 · Guest teaching 0/10 Unlocking First-Party Dark Data and Medical Insights Chen uses case studies on death certificates and East African vaccination registries to illustrate dark data normalization. The host is non-participatory.16:17–19:39 · Guest teaching 2/10 Strategic Enterprise Benefits of Normalized Data Matt Turck steps in at the end of the presentation to ask about the human and social engineering aspects of enterprise AI sales. Chen agrees and expands on buyer skepticism, resulting in a cooperative interaction.19:39–23:53 · Guest teaching 7/10 Q&A on Cloud Security and Machine Intelligence Architecture Turck asserts that enterprise deployments must be on-premise, but Chen corrects him by stating Captricity is 100% cloud-based. Turck adapts and pivots to ask about Fortune 1000 cloud security concerns.0:53–4:34 · Guest disagreement 1/10 State of the Enterprise and Rising Business Uncertainty This segment is a presentation monologue by Kuang Chen introducing the macro challenges facing enterprises. The host does not participate, requiring zero host-side scores.4:34–6:48 · Guest disagreement 0/10 Case Study on Netflix Data Transformation and AI Strategy Chen delivers a solo presentation detailing Netflix's evolution from DVD mailing to data-driven content creation. As a pure monologue segment, host metrics remain zero.6:48–9:11 · Guest disagreement 1/10 Key Solution Criteria for Successful Enterprise AI Chen presents solution criteria for enterprise AI, focusing on first-party dark data and high accuracy thresholds. The host remains silent throughout.9:11–13:58 · Guest disagreement 0/10 Captricity Enterprise AI Infrastructure Architecture Chen explains Captricity's architectural layout and human-in-the-loop dynamic training system. The host does not join the discussion.13:58–16:17 · Guest disagreement 0/10 Unlocking First-Party Dark Data and Medical Insights Chen uses case studies on death certificates and East African vaccination registries to illustrate dark data normalization. The host is non-participatory.16:17–19:39 · Guest disagreement 1/10 Strategic Enterprise Benefits of Normalized Data Matt Turck steps in at the end of the presentation to ask about the human and social engineering aspects of enterprise AI sales. Chen agrees and expands on buyer skepticism, resulting in a cooperative interaction.19:39–23:53 · Guest disagreement 2/10 Q&A on Cloud Security and Machine Intelligence Architecture Turck asserts that enterprise deployments must be on-premise, but Chen corrects him by stating Captricity is 100% cloud-based. Turck adapts and pivots to ask about Fortune 1000 cloud security concerns.0:53–4:34 · Matt pushing back 0/10 State of the Enterprise and Rising Business Uncertainty This segment is a presentation monologue by Kuang Chen introducing the macro challenges facing enterprises. The host does not participate, requiring zero host-side scores.4:34–6:48 · Matt pushing back 0/10 Case Study on Netflix Data Transformation and AI Strategy Chen delivers a solo presentation detailing Netflix's evolution from DVD mailing to data-driven content creation. As a pure monologue segment, host metrics remain zero.6:48–9:11 · Matt pushing back 0/10 Key Solution Criteria for Successful Enterprise AI Chen presents solution criteria for enterprise AI, focusing on first-party dark data and high accuracy thresholds. The host remains silent throughout.9:11–13:58 · Matt pushing back 0/10 Captricity Enterprise AI Infrastructure Architecture Chen explains Captricity's architectural layout and human-in-the-loop dynamic training system. The host does not join the discussion.13:58–16:17 · Matt pushing back 0/10 Unlocking First-Party Dark Data and Medical Insights Chen uses case studies on death certificates and East African vaccination registries to illustrate dark data normalization. The host is non-participatory.16:17–19:39 · Matt pushing back 2/10 Strategic Enterprise Benefits of Normalized Data Matt Turck steps in at the end of the presentation to ask about the human and social engineering aspects of enterprise AI sales. Chen agrees and expands on buyer skepticism, resulting in a cooperative interaction.19:39–23:53 · Matt pushing back 4/10 Q&A on Cloud Security and Machine Intelligence Architecture Turck asserts that enterprise deployments must be on-premise, but Chen corrects him by stating Captricity is 100% cloud-based. Turck adapts and pivots to ask about Fortune 1000 cloud security concerns.

speaking balance: gold is Matt, purple is the guest (3 minute bins)

0:00 · Matt 0% · guest 100%0:00 · Matt 0% · guest 100%3:00 · Matt 0% · guest 100%3:00 · Matt 0% · guest 100%6:00 · Matt 0% · guest 100%6:00 · Matt 0% · guest 100%9:00 · Matt 0% · guest 100%9:00 · Matt 0% · guest 100%12:00 · Matt 0% · guest 100%12:00 · Matt 0% · guest 100%15:00 · Matt 3.1% · guest 96.9%15:00 · Matt 3.1% · guest 96.9%18:00 · Matt 31.1% · guest 68.9%18:00 · Matt 31.1% · guest 68.9%21:00 · Matt 20.5% · guest 79.5%21:00 · Matt 20.5% · guest 79.5%
Sharpest disagreement ▶ 21:05 Polite correction on cloud architecture

Chen directly counters the host's confident assumption that enterprise data needs on-prem deployment by noting Captricity is entirely in the cloud.

 Hardest push from Matt ▶ 21:09 Challenging enterprise readiness for cloud

After being corrected on cloud usage, Turck pushes back by questioning whether large Fortune 1000 companies are truly ready to move sensitive data to cloud providers.

 Biggest teaching moment ▶ 20:51 On-premise assumption debunked

Turck confidently asserts that Captricity must operate on-prem due to data sensitivity, forcing Chen to inform him that they operate entirely in the cloud.

 Matt holds his own ▶ 17:54 Highlighting organizational adoption hurdles

Turck demonstrates enterprise sales insight by shifting focus from technical capabilities to human politics and organizational adoption.
the scores for every segment, with the reasoning behind each
ChapterTopicMatt as informed peerGuest teachingGuest disagreementMatt pushing backWhy
State of the Enterprise and Rising Business Uncertainty 0010 This segment is a presentation monologue by Kuang Chen introducing the macro challenges facing enterprises. The host does not participate, requiring zero host-side scores.
Case Study on Netflix Data Transformation and AI Strategy 0000 Chen delivers a solo presentation detailing Netflix's evolution from DVD mailing to data-driven content creation. As a pure monologue segment, host metrics remain zero.
Key Solution Criteria for Successful Enterprise AI 0010 Chen presents solution criteria for enterprise AI, focusing on first-party dark data and high accuracy thresholds. The host remains silent throughout.
Captricity Enterprise AI Infrastructure Architecture 0000 Chen explains Captricity's architectural layout and human-in-the-loop dynamic training system. The host does not join the discussion.
Unlocking First-Party Dark Data and Medical Insights 0000 Chen uses case studies on death certificates and East African vaccination registries to illustrate dark data normalization. The host is non-participatory.
Strategic Enterprise Benefits of Normalized Data 3212 Matt Turck steps in at the end of the presentation to ask about the human and social engineering aspects of enterprise AI sales. Chen agrees and expands on buyer skepticism, resulting in a cooperative interaction.
Q&A on Cloud Security and Machine Intelligence Architecture 4724 Turck asserts that enterprise deployments must be on-premise, but Chen corrects him by stating Captricity is 100% cloud-based. Turck adapts and pivots to ask about Fortune 1000 cloud security concerns.

Statements from this episode (12)

Assertion Not checkable as stated
Chen: Regulated industries rank worst at customer service despite prioritizing it
“Many of our customers in the regulated industries, government healthcare, insurance they say that customer service is their number one priority, bar none. And yet they're also ranked among the worst at it.”
Kuang Chen Mar 24, 2017 ▶ 1:53
Assertion Not checkable as stated
Chen: Legacy enterprise software was built for compliance, not for AI
“The systems that they have with which to work with were built maybe 10, 20, 30 years ago, and those systems were built for let's call it compliance, and for workflow efficiency, and not for the age of big data and AI and being able to look across workflows.”
Kuang Chen Mar 24, 2017 ▶ 2:59
Insight
Chen: High legacy IT maintenance costs leave enterprises unable to innovate
“Legacy IT costs Costs are so high that there's really not a lot of budget with which to innovate, and it makes it so that it's really hard to change anything, and so as customers' expectations of the input methods evolve these organizations, these incumbents a…”
Kuang Chen Mar 24, 2017 ▶ 3:45
Insight
Chen: Enterprise AI solutions must hit 99.9% accuracy from day one
“Solutions need to be 99.9% in accuracy right out of the gate from day one in order to be really effective”
Kuang Chen Mar 24, 2017 ▶ 8:21
Assertion Not checkable as stated
Chen: Large regulated enterprises struggle significantly to recruit machine learning talent
“In large regular enterprise, it's really hard to hire machine learning talent.”
Kuang Chen Mar 24, 2017 ▶ 8:40
Assertion Not checkable as stated
Chen: Captricity has effectively solved the handwriting recognition problem
“We've effectively solved the handwriting problem.”
Kuang Chen Mar 24, 2017 ▶ 9:58
Assertion Not checkable as stated
Chen: Captricity is near 99.9% accuracy in voice transcription
“We're well on our way to solve 99 point nine percent voice transcription.”
Kuang Chen Mar 24, 2017 ▶ 10:01
Assertion Not checkable as stated
Captricity helped PATH implement a vaccine intervention within weeks
“And one of our customers, PATH, a great non-profit, they were able to, within weeks of sending us these images, put into place an intervention that drastically altered the way that they were thinking about the monitoring and evaluation of this vaccine program.”
Kuang Chen Mar 24, 2017 ▶ 14:23
Assertion Not checkable as stated
Captricity data shows secondary death causes are chronic, primary are sudden
“But what we also found was that those secondary causes of death tend to be the chronic conditions, whereas the primary cause of death tends to be sort of the ambulatory or the sudden conditions, like what happens in the hospitals.”
Kuang Chen Mar 24, 2017 ▶ 15:29
Insight
Chen: Large regulated enterprises are skeptical of AI hype and focus on business outcomes
“A lot of large regulated enterprise just is skeptical. They're well aware of the hype, and they can also kind of feel just how far away it is from their own day-to-day reality, and so, as you can see by the way that we talk about the solution we have to come a…”
Kuang Chen Mar 24, 2017 ▶ 18:56
Insight
Chen: For large enterprises, AI is secondary to reducing operational costs
“At the end of the day running a large public regulated enterprise it's all about being able to reduce the cost of operations being able to target new customer segments. Having AI is is a cherry on top.”
Kuang Chen Mar 24, 2017 ▶ 20:23
Assertion Not checkable as stated
Chen: Captricity has never lost a customer over cloud security concerns
“We've never lost a customer to an unwillingness to put their customer data behind our firewall.”
Kuang Chen Mar 24, 2017 ▶ 21:23
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