Shahriar Tajbakhsh, Co-founder & CTO of Metaview: BREAKING: Metaview acquired Reval

0:00Scaling Europe:Hello, welcome back to Scaling Europe show. I'm Sib Jolson. Today on the show, I've got Shorai, co-founder, CTO of MetaView. How are you doing today? Doing great. Thanks for having me. My absolute pleasure. Look, you've just announced this very exciting acquisition. But before we get into that, can you give maybe a super quick intro into MetaView and what you've built? Yeah, we have built a platform for recruiting with AI at its core. The idea is that we want to be able to deliver end-to-end recruiting outcomes to every company in the world. And we think the best way to do that in a 100x or 1000x or 10 ,000x manner relative to the past is by having AI be at the core of all of the workflows that get done in recruiting to help superpower humans to do more of the things that they're good at and much less or fewer things that AI and computers are much better at.

0:58And so that's what we're doing, just drastically increasing leverage for our customers so that they can make great hiring decisions.

1:05Scaling Europe:And can you talk maybe a bit about where you're at today? Because I know that you're working with thousands of companies, including some of the most exciting tech companies in the world. Can you maybe give a brief overview of where you're at in your journey yeah we are uh working with just over 5 000 companies uh in the world that number is uh kind of pretty rapidly expanding um across many different industries many of the names that uh you would have heard of as kind of luminary uh companies within their own industries including tech and silicon valley um but also although many other kind of niche companies that maybe amongst the consumers are not well known but they are nevertheless creating a lot of impact in the world and need to hire, I need to hire fast, I need to hire effectively.

1:53We work with almost everyone. If you need to make hires, especially within the knowledge work sphere, then MetaVive will make life better for you.

2:06Scaling Europe:and can we talk a bit about film more specifically so film was kind of your autonomous ai co-worker but it's relatively new can you touch on that and then we can get into the acquisition and where that fits within film yeah so film more is our kind of first principles approach to kind of taking the taking the step back and thinking if given the capabilities available today technologically speaking given our understanding of the this domain which is recruiting. If a product was designed today from scratch with no baggage of history to completely change people's lives as it pertains to recruiting, what would it be?

2:46And the answer to that is Fillmore. So the best way to think about Fillmore is it is just a co-worker. In the same way that you have Fillmore as an I have co-worker, Fillmore is your co-worker. It happens to be AI, but the way it fills and it interacts and it asks questions and it responds to questions it is identical to a co-worker you speak to Fillmore on Slack Fillmore speaks to you on Slack Fillmore does work hours and hours a day all the time 24-7 and at the moment Fillmore have has one objective which is to take whatever context that you have available for a role that you're hiring for. Let's say you're hiring for a staff software engineer and you have a job description for that and maybe an intake call with a hiring manager and or any other kind of artifact that helps you know what it is that you're looking for and what kind of canvas you want.

3:45The input to Fillmore is that set of artifacts. It could be as small or little as a job description. It could be anything else that you have. And from then on, Fillmore will autonomously, without any human intervention, essentially completely long time horizon task, which is figuring out what kinds of profiles you're looking for, running market research across maybe 50 different strategies of research to figure out what does the market look like for this particular role, where a company is similar to you hiring from, where's their talent going to, just doing a whole bunch of analyses. The outcome of those analyses results in feel more than deciding what the best sourcing strategies are.

4:27So maybe it will come up with 100 different sourcing strategies and in parallel perform those. So each of those results in a bunch of candidates. Again, all of this happening automatically. Then Philmore will spin out, let's say it's just found 200 candidates that might be appropriate. It will spin out 200 agents and at the same time run deep research into each individual candidate, figure out what they're about, essentially learning everything there is to know about that candidate on the internet with the goal of deciding what is the best way to reach out to them for a particular role. It will then do that.

5:05It will then across email, LinkedIn, and WhatsApp decide what the best method of reaching out to them is completely personalized in a personalized manner, curate the message that needs to go out for them. no two candidates get the same thing every candidate gets messages or communication that is completely empathetic to their background that what they're interested in and what they want to hear about and the goal is to book meetings with these candidates with hiring managers and recruiters for our customers and today that is what Fulmo does and over time it will do more and more of the workflow completely autonomously.

5:48And so in summary, Fillmore is just like your coworker. You say what you want. It goes and works nonstop and books meetings in your diary. Zero human intervention. And it's the most magical product we have built to date. It's been kind of soft launched with a bunch of customers the past eight to ten weeks. and we've never seen anything like it in terms of the performance that it has and the

6:17Scaling Europe:like uptick and growth let's talk about the performance in the great before we do can we talk on the framing as a co-worker because i really like that it's a co-worker and it's very different from a lot of ai recruiters or ai agents that we're seeing in the market today why did you go out and decide to build something that was more robust why was that needed rather than like a more basic agent um i don't i don't think there was a it's not that we sat down one day and decided this is it has to be a core recent agent i just think that is the thing that makes sense uh work needs to get done uh it is now possible if you know what you're doing uh to have ai do a lot of work given if it's put in the right harness in the right environment given the right tools and capabilities.

7:04And so at that point it is just indistinguishable from a colleague. Um, and I, I, I honestly can't think of any other frame, uh, frankly, it's like an agent feels a bit weird. Um, I don't call you an agent when we work together, you know, you just, he's just a colleague, we hang out. We, I ask you stuff, you ask me stuff, you go and work. Uh, and that's really what, how FIMO operates. And I think that operating model works really well because that is how we are used to working as people in every company. We're used to working with a bunch of colleagues and when they need our help they come to us and when we need their help we go to them.

7:39And at least a large portion of communication as it pertains to work happens on Slack and Teams and that's also where Plummel operates as opposed to being this kind of separate UI or web app or whatever. That's kind of weird if you think about it that you have to go to a separate product to like press buttons uh that's like very 2024 i think yeah today what gets done in slack film what comes to slack it gets it done and uh it kind of gets out your way just like a good collie

8:07Scaling Europe:yeah yeah everything lives in slack these days um let's talk about the detraction then so you launched it you know two just over two months ago it's very soft launch have is has that been with existing customers only or have you kind of taken that outside that initial group as well and then what have the results been we have unfortunately i can't talk about much of the the traction with quantifiable numbers just because they are so unbelievably good that I don't want anyone any ideas about how like this could be but suffice it to say we initially started alpha testing with a very select few customers we instantly saw insanely good results I'll give one anecdote.

8:52A particular model lab that we worked with was looking for LLM researchers and staff software engineers. Those are roles that typically, on average, they're different for each role, but it typically takes 90-ish days to fill for them. And they made a number of hires with fill more in between 40 and 50 days. So that's kind of half that time. One of the candidates, they said it's the best candidate they have ever met. This is an AI lab with the highest bar possible. And Phil Moore has managed to find, engage, and get the candidate on a call in a role that is highly sought after with insane compensation.

9:44So it's not that these people are sitting, they're desperate for a job. but the quality and the caliber of the outreach that Fillmore had done based on the research they had done reading their papers, going through their podcasts listening to their podcasts looking at commit messages on GitHub the kind of stuff they're contributing to the kind of work they're doing all of that resulted in engagement and a happy company with a phenomenal candidate and a happy candidate that is a company now that's a bit to fit with them that's like one anecdote we have many many of these examples initially with alpha customers then kind of in a beta phase where we introduced it to more of our existing customers and it's been now a number of weeks where we have a whole bunch of new folks on the product and we're helping companies you know give offers and have offers accepted literally like every day now um and it's it's awesome and the thing that one of the things that particularly there's a bunch of quantifiable stuff that all those numbers are impressive and like really nice to look at but the softer parts of it is also really encouraging and inspiring and energizing which is the number of candidates that tell our customers how impressed they were with the quality of the reach out to them and their responsiveness and just the general candidate experience, which is kind of, I think, to more legacy-minded people is counterintuitive.

11:20They think if an AI is doing the work, it feels impersonal, etc. It's actually the opposite, right? And you now, instead of having one recruiter, having to juggle 200 candidates and talking to them and reaching out to them, you have each candidate essentially has their own AI that white glove treats them replies to them within 30 seconds shares context is like nice all the time um and speaks the way they want to be spoken at not in like some generic way uh anyway results have been outstanding super i'm just like very very pumped about um the this like new new shift that's gonna happen in the industry because of film that's amazing yeah i mean it's uh i can imagine as a candidate that it's a much better experience

11:59Scaling Europe:you know having somebody immediately responsive who actually knows because i guess like a lot of outreach that i know that i've experienced has been like terrible fit you know you you get a message yeah and it's like that's this is completely irrelevant and like linkedin is the worst example where like recommend your job and it would be like fireman in north hampshire or something and i'm like what the how is this a good job relevant for me um can we talk about the acquisition then like who have you acquired and why and how is this going to fit into the Fillmore strategy going forward? Yeah, so we recently acquired Reval.

12:31The team there has been working on an AI recruiter for a number of years now, similar to Fillmore, different approach like implementation-wise, but ultimately the same outcome that thereafter. They had built a completely AI first and AI last recruiting agency where they were operating essentially as an agency except with AI running the show as opposed to the traditional way, which is how much money you can make or how many roles you can serve was directly correlated to how many people you could hire or how many recruits you can have on your team. Reval wasn't like that. They could essentially have capacity to manage infinite roles because the agency from the ground up was built to be run by AI.

13:19We were generally just largely aligned with where we think the recruiting industry is headed and should be going. They have a phenomenal team. We happen to be slightly ahead in terms of just the maturity of our company. And we have phenomenal distribution and brand recognition and access to lots and lots of customers. It just made sense to team up to bring the incentive of talent that Rival has with the mission alignments that we both have together and, you know, start pushing like one ball instead of two separate balls in the same direction. We all want the same thing. So I think together we're going to end up being significantly more likely to the change world.

14:14Scaling Europe:And how long have you known the team? Have you been looking at them, talking to them for a while? how did this sort of like opportunity arise to team up like this serendipity largely uh we have been i think the the world is quite small you're always aware of everyone and what they're up to especially in the in like the product and startup world so we we we have been aware of each other uh but more recently we just we we just like realized through conversations where we want the We are trying to build the same future and it is just a no-brainer to apply that like joint forces and do that with MetaView's existing ability to have impact and distribute product.

14:55And so the road for Reval on their own would have been a bit of an uphill battle to be able to get the market penetration that they should get. and we could just remove that as a risk and the same talent can not worry about getting initial traction but we already have traction and we could only focus on building a phenomenal product that is Fillmore and we'll get exactly the outcome that they want that we want we all want some outcome which is to make this industry significantly more leveraged and so just like more recent conversations it's very obvious that that's like a no-brainer

15:36Scaling Europe:And you've obviously raised, I think, over$40 million now from the likes of plural, I think, Google Ventures. Pretty well capitalized. Is this a potential strategy going forward? Do you see yourself making more acquisitions in this space where it can make sense? Totally. I think we may or may not be significantly better capitalized than you mentioned. But yeah, I think that's the name of the game. If we think joining forces with other folks will increase our likelihood of winning, then we will do that. We basically have a lot of power in front of cash to do that. And so we're always on the lookout, especially for phenomenal teams.

16:20I think it's all about the team quality for us. And we're hiring heavily. We can't hire fast enough. and when you find another phenomenal team that's mission aligned that's kind of a cheat code to hiring right you can get you know that many people in at once and you're all aligned and you know they're phenomenal in in whatever competency that they have and so i just think it's a it's a really good way to to accelerate hiring um and also accelerate rate of learning so you know we're there's a whole bunch of stuff that reval has learned uh through their approach to product which is actually different to how we had done it and those learnings essentially come for free obviously it's not free the acquisitions cost money but you just accelerate that process so yeah we're always always looking and it looks like they're bringing some interesting skills or

17:18Scaling Europe:part of the stack in terms of like helping with sourcing i guess on some of the more yeah the ai stuff that they've built where do you see metaview and film all going in the next 12 or 24 months across that whole recruiting stack or process are there parts of the process where you think actually that we're never going to touch that that'll always be humans or do you think actually there's a role for metaview and ai across every layer of the recruiting stack i think uh maybe i'll uh re kind of reframe the question or like answer it in a reframe manner the thing that MetaView partially is today, but indubitably will be in a year, is the platform where end-to-end recruiting outcomes get delivered.

18:00That is, from the moment you are looking for a role as a company to the moment a person, a butt is in seat. There's a shit ton of activity and workflows and work that needs to happen for this end-to-end recruiting outcome to occur. And MetaView will be the singular platform where every single one of these activities will happen on. And because it will be the singular platform with one source of truth for context and where all the work will get done, that results in just a significant leverage increase. And therefore, companies can hire phenomenal talent significantly faster than they can today now which parts of this platform will be a ai fully ai operated versus partially operated versus human operated that's kind of irrelevant if you think about a bunch of forms of intelligence have to do work to get this work done to this to get this internet recruiting outcome done some of that intelligence happens to be biological in the form of humans.

19:09Some of it will happen to be silicon. It doesn't really matter. We're thinking about the work that needs to get done and what kind of worker is best positioned to finish or complete that work as fast as possible with the highest quality. Oftentimes it's turning out that an AI worker happens to be very good and won't position to do that. But there are certain instances where biological compute or the human brain is just significantly better today. Maybe that'll be different in a year, but it almost doesn't matter. It's all about the internal recruiting outcome and delivering that in as leveraged way as possible.

19:50I happen, if I was to predict, I think a significant portion of it will be done by AI.

19:56Scaling Europe:Amazing. And look, one final question. In 6, 12, 18 months, what needs to happen? What do you need to achieve to make the Reval acquisition have been an incredible success? I think the Reval acquisition has been an incredible success. Today is day three. And the team has already been shipping to production and contributing to our product. As we expect anyone that joins the company, people start shipping from day one. And it's very clear from the contribution on three days that we have added phenomenal sets of talent to our team. Reval is a success. We're going to wait six to eight months. Amazing, Willett.

20:36Scaling Europe:Thank you so much for joining me. congratulations uh i'm sure there's going to be lots more exciting news coming from you guys soon so um i'll be on the lookout awesome thanks for uh taking time