Connect with us


Six imperatives for building AI-first companies



Change happens slowly, and then all at once — especially in complex industries like healthcare.

Just five years ago, venture capital investments in healthcare AI were emerging and exploratory. Half a decade and one global pandemic later, we’re living in a brave and more ambitious new world defined by an unbridled enthusiasm for leveraging revolutionary technologies like AI.

Pointing this technology at previously intractable problems in key industries such as healthcare, life sciences, and beyond is among the greatest opportunities of the century.

The year 2022 was when the broader public bore witness to material advancements in AI research that have matured from lab to life. ChatGPT educated over 100 million people globally about transformers in just two months.

What was once a nascent area of research has now become venture capital’s next platform shift, and with that, investors ask, “How will generational AI companies be built in healthcare, life sciences, and beyond?”

AI-first companies are in the business of advancing AI as a science, whereas AI-enabled companies are implementation and distribution machines. The two company phenotypes establish moats at different layers — AI-first companies innovate just above silicon, while AI-enabled companies create enterprise value at the application level.

For founders, knowing what kind of company you are building is essential for recruiting proper talent, partnering with aligned investors, securing sufficient capital, and deploying a viable business model. AI-first companies require deep AI research acumen, investors willing to take a long view, materially more capital, and potentially less conventional business models than AI-enabled peers.

The impact of AI-first companies will be greater, financial returns superior, and moats more enduring than their AI-enabled counterparts.

In reality, this distinction is a spectrum, not a binary. Impactful companies will be built with both approaches. For AI-first companies, though, we believe the fruits will be worth the labors.

Influence over the technology stack from the ground up enables tight control over cost structure, immeasurable product optionality, and greater defensibility relative to AI-enabled companies that defer the exercise of scientific inquiry to those that are AI first.

We can no longer afford to conflate AI-first and AI-enabled companies. So far, the largest AI-first companies have been built for horizontal applications (e.g., OpenAI, Cohere, Anthropic); yet vertical, industry-specific platforms, such as those in healthcare and life sciences, will showcase the expansive capabilities of large-scale models to deliver real-world impact.

For founders, we believe enduring AI-first companies — in healthcare, life sciences, and beyond — will follow these six imperatives.

Create and sustain an undeniable data advantage

AI-first companies exhibit an insatiable appetite for data and employ creative means for acquiring it sustainably. In addition to amassing large and robust datasets, AI-first companies develop designer datasets that are uniquely suited to deliver high performance on specific tasks.

Designer datasets are unique in that they are not easily found in public; they are machine readable, in that they are ingestible by AI models; and they are scalable, in that it is tractable to generate high volumes over time.

Importantly, designer datasets are not simply the exhaust of processes within a given system, and they are not generated by customers alone. For example, the healthcare and life sciences industries generate 30% of the world’s data, and yet companies that train only on existing electronic health record data or resources like PubMed leave material performance gains and capabilities behind.

Designer datasets may require authoring experimental protocols for situations that do not occur naturally but that deliver strong model performance for a given task.

For example, Subtle Medical, an AI-first company focused on imaging acceleration, generated millions of imperfect MRI images captured in 15 minutes, which were later utilized to train deep learning models that could reconstruct and de-noise medical imaging exams taken in shorter periods of time. In practice, imperfect MRI images provide little clinical value; however, as an AI-first company, these images trained deep neural networks that created a data moat for Subtle’s technology.

Reinforcement learning with (expert) human feedback — RL(E)HF — is another critical tool for AI-first companies. RLHF is a technique where an AI system learns and improves its performance by receiving feedback from human input. With RL(E)HF, expert human feedback provided by individuals trained in particular disciplines such as neurology or structural biology can tune model outputs for high performance in that domain.

Abridge, an AI-first company that provides ambient documentation tools for clinicians, leverages clinician feedback on AI-authored notes to enhance note accuracy and quality across specialties.

Data derived from customers also creates flywheels of opportunities for generating novel and defensible data assets. After establishing product-market fit, AI-first companies can leverage this position to serve adjacent customer segments. By capturing and integrating datasets across stakeholders in a given industry, AI-first companies can strengthen data advantages, unlock TAM, and create new categories.

Recruit and empower AI scientists

Source link

Continue Reading
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *


MoneyHash raises $4.5M for its payment orchestration platform serving merchants in MENA




The payment landscape in the Middle East and Africa (MEA) region is marked by significant fragmentation, with numerous payment providers and methods in each country, evolving regulations and diverse customer preferences. This complexity is further compounded by challenges such as payment fraud, low checkout conversion rates and high transaction failure rates.

Although the COVID-19 pandemic accelerated the adoption of digital payments in the region, infrastructure development remains inadequate. Payment failure rates are three times higher in the MEA region than the global average, and fraud rates and cart abandonment exceed those of other regions by more than 20%. This presents a challenge for merchants, who often perceive payments as a cost and risk center rather than a strategic enabler.

Payment orchestration platforms streamline payment processes for merchants through unified payment APIs. Egyptian fintech MoneyHash, one of such in Africa and the Middle East, has raised $4.5 million in seed investment, money it plans to use to further invest in its technology and growth across the region. This comes two years after the startup secured $3.5 million in pre-seed.

Nader Abdelrazik, co-founder and CEO of MoneyHash, highlights that 10% of all payments processed in the MEA region are digital, placing MoneyHash uniquely for a growth phase that the region will inevitably experience over the next decade. However, navigating this burgeoning payments market will demand patience and a commitment to continuous learning.

As merchants or companies launch their platforms, they often start by collaborating with one or two payment processing providers. As their operations grow and expand into multiple regions, they onboard additional payment providers to meet their evolving needs. However, integrating different payment stacks presents significant challenges. Besides the operational inefficiencies and technical complexities, in-house tech teams may take several weeks to complete these integrations. In Africa and the Middle East, these challenges are amplified by variations in payment methods, currencies and the isolation between countries.

MoneyHash payment integration catalogue. Image Credits: MoneyHash

MoneyHash’s product includes a unified API to integrate pay-in and pay-out rails, a fully customizable checkout experience, transaction routing capabilities with fraud and failure rate optimizers and a centralized transaction reporting hub. This is complemented by tools enabling various use cases such as virtual wallets, subscription management and payment links. Fintechs such as Revio, Stitch, Credrails and Recital are similar players in the payment orchestration space.

In an email interview with TechCrunch, Abdelrazik shared insights into MoneyHash’s collaboration with merchants over the last four years. For one, he claims that payment failure rates across the region vary significantly, and relying solely on averages can be misleading. While the typical figures are around three out of 10 payments failing on average, the reality differs widely among businesses, he said. For some, it may be as low as one out of 10, while for others, it could be as high as five or six out of 10. Additionally, these figures do not include customers who abandon the checkout process voluntarily before making a payment. The CEO also noted that most of its customers don’t know much about the complexity of payments and, many times, are not aware that most leakages they have in payments are fixable.

Furthermore, merchants are expanding much faster than their partner payment service providers (PSPs). These PSPs operate under stringent regulations, making the rollout of new products and customizations slower than the merchants’ growth trajectory. As a result, MoneyHash has intensified its collaboration with PSPs, particularly those catering to enterprises and prioritizing customer requirements.

“Businesses appreciate the large network of integration we have not just for coverage but for expertise. When they know that we executed all these integrations in-house, they appreciate the team’s expertise and depth of knowledge and leverage our team to navigate difficult questions in payments. They know that working with us makes them future-proof,” noted Abdelrazik, who founded MoneyHash with Mustafa Eid.

“That means team expertise is key for us. Most of the time, we hire exclusively with payments and/or tech backgrounds, even in non-technical positions. We saw massive effectiveness in building a team where customers trust their knowledge and expertise in something specialized and critical like payments.”

Following a beta launch in 2022, which garnered the participation of key regional players like Foodics, Rain and Tamatem, MoneyHash introduced its enterprise suite last October, targeting large enterprises. Over the past year, the fintech, which integrates with various payment gateways and processors, including Checkout, Stripe, Ayden, Amazon Pay, Tap and ValU, claimed to have expanded its network of integrations, tripled its revenue and increased its processing volume by 3,000%.

At present, MoneyHash boasts 50 active paying customers. It does not offer free tiers; most customers accessing its sandbox without payment are potential clients in the assessment stage, numbering over 100. The payment orchestration platform levies a combination of SaaS and transaction fees, commencing at $500 + 0.4%. SaaS fees increase while transaction fees decrease significantly for large enterprises due to volume, Abdelrazik explained.

MoneyHash’s seed round was co-led by COTU Ventures and Sukna Ventures, with participation from RZM Investment, Dubai Future District Fund, VentureFriends, Tom Preston-Werner (GitHub’s founder and early Stripe investor) and a group of strategic investors and operators.

Speaking on the investment, Amir Farha, general partner at COTU, said his firm believes that the full potential of digital payments in MEA is yet to be realized and MoneyHash’s platform can catalyze the growth of digital payments across the region, enabling both global and local merchants to tap into new revenue streams. “We are thrilled to renew our support to a team that has consistently demonstrated superior execution, not just in securing top mid-market and enterprise customers, but also in expanding value across the entire chain, even under challenging market conditions,” he added.

Source link

Continue Reading


Snowflake CEO Frank Slootman stepping down — and Wall St hates it




Apparently Frank Slootman, the veteran tech executive, was popular with investors, at least judging from their reaction that he will be stepping down as CEO of Snowflake. The company stock price has plunged more than 24% in after-hours trading on the news.

Slootman will retreat into the role of chairman of the board, while Sridhar Ramaswamy, former head of Google Ads, who came to the company when it bought AI search engine Neeva last year, will take over as chief executive.

Lost in today’s executive shuffle was the company’s earnings. It reported revenue of $738 million, up a healthy 33% year over year with guidance for the next quarter of between $745 and $750 million, with growth of 26-27%.

Slootman came on board in 2019, taking over for veteran executive Bob Muglia, and was charged with taking the company public the following year. Over the last year, the stock has done well, up around 50% (the exact amount is hard to tell with this afternoon’s downward spiral), as many tech stocks recovered from 2022 doldrums.

He was famously well-compensated, with a base salary of $375,000 and a rather attractive stock option. In fact, Fortune reported that the chief executive was making an eye-popping $95 million a month at one point.

He raised eyebrows in 2021 when he told a reporter that diversity shouldn’t override merit, and eventually walked back those comments after a negative reaction from industry peers.

Prior to coming to Snowflake, he spent six years as chairman and CEO at ServiceNow. With all that cash, perhaps he’ll retire and enjoy his money.

Source link

Continue Reading


Fintech giant Stripe’s valuation spikes to $65B in employee stock-sale deal




Payments infrastructure giant Stripe said today it has inked deals with investors to provide liquidity to current and former employees through a tender offer at a $65 billion valuation.

Notably, the valuation represents a 30% increase compared to what Stripe was valued at last March when it raised $6.5 billion in Series I funding at a $50 billion valuation. But it is also still lower than the $95 billion valuation achieved in March of 2021.

While Stripe declined to comment beyond a written statement, a source familiar with the internal happenings in the company told TechCrunch that Stripe and some of its investors agreed to purchase over $1 billion of current and former Stripe employees’ shares.

The company, which counts the likes of Alaska Airlines, Best Buy, Lotus Cars, Microsoft, Uber and Zara as customers, had noted at the time of its last raise that the proceeds would go to “provide liquidity to current and former employees and address employee withholding tax obligations related to equity awards.” That, it added, would result in the retirement of Stripe shares that would offset the issuance of new shares to Series I investors.

A Stripe IPO has been long anticipated and was widely expected to happen in 2024. But with this deal, it appears that an initial public offering may not take place until next year.

In January, TC’s Rebecca Szkutak reported that — in anticipation of that IPO and according to secondary data tracker Caplight — there had been “an absolute flurry of buyers looking to get shares in the company in recent months.” On January 2, a secondary sale closed that valued Stripe shares at $21.06 apiece and valued the startup at $53.65 billion, according to Caplight data.

While Stripe did not name the investors participating in the latest deal, Sequoia Capital Managing Partner Roelof Botha was quoted in Stripe’s announcement and The Wall Street Journal cited Goldman Sachs’s growth equity fund as another backer.

The WSJ also reported that the transaction “is part of a commitment by the Collison brothers to provide liquidity annually to longtime and former employees.” Sources familiar with internal happenings at the company said that commitment is more to provide liquidity “regularly,” and not necessarily annually.

Want more fintech news in your inbox? Sign up for TechCrunch Fintech here.

Source link

Continue Reading


Copyright © 2023 Dailycrunch. & Managed by Shade Marketing & PR Agency