This is the application which got us to the final round the second time in the same year
Gig platform for industry experts
We are building a (1) One stop shop for hiring industry experts for consultatons with (2) service levels of high cost expert networks like GLG at much lower prices made possible by (3) intelligent expert finding algorithm and complete process automation. Companies simply need to post their expert requests to us in plain text and once we find the right experts, we bring them onboard to fulfil the client request. We do it faster (in 24 hours) and cheaper (at least by 50%) than similar companies
Companies require industry experts for specialized tasks usually when they don’t have in-house expertise. E.g. Setting up a dairy plant, data analytics experts, industry sales veterans for startups etc. Companies have difficulty finding experts who they trust to do the job and experts also don’t have access to high quality gigs. This is the problem we are attacking.
As of now we have automated profile searching on large databases like linkedin and catering to more than 200 consulting hours monthly. Our search is being trained with new requests everyday and as demand grows, we will adapt to search on other databases like indeed etc. After achieving a critical mass of requests, we will transition to a full platform by having experts sign up with their profiles and receive well matched consulting assignments automatically
Abhishek and Ramkesh worked on a student engagement portal in IIM Calcutta. The portal had sections on course notes and book scans, previous batch question papers, previous placement interview questions, daily mess menu and grievance redressal.
The administration of the portal was handled by respective student secretaries — academic, mess and placement secretaries. The student community found it very useful, however the portal was discontinued two years later as the institute outsourced a complete institute ERP system and was not willing to pay for the storage and maintenance cost of this portal
Aditya and Abhishek met through a common friend and worked on a remote working platform for out-of-work housewives (Zorkr) in parallel to Vedak. However after that did not work out, they decided to join hands to build Vedak. That was a year back.
Ramkesh and Abhishek knew each other in IIM Calcutta where they worked on a student engagement portal. Ramkesh is managing the tech stack at Vedak and joined full-time 3 months back.
Our team is now fully formed with the right mix of business, technical and operations expertise.
We have just launched an expert search engine (demo) which is successfully automating our requests thus dramatically reducing cost and time of fulfilment. This has created the ideal launchpad for us to launch operations globally
We have serviced more than 1000 consulting hours till date bringing in around two hundred thousand dollars in revenue at 38% gross profit.
We started taking orders in June 2016 and have consistently grown at average of 15% MoM by word of mouth. Aditya and Abhishek have been working on this for more than a year full time and Ramkesh (tech) for 3 months full time
We have 15 active enterprise customers. Some are among the largest consulting and PE firms like McKinsey, Ernst & Young, Bain &Co, TA Associates, Matrix Partners.
The last time we interviewed for S17, we were given two pieces of feedback. First — Can this be automated, Second — figure out a distribution strategy
For the first feedback, we have worked to build a product which can search through millions of profiles and get us the precise match. Thus we can scale to manage hundreds of requests a day. On the second feedback, we have worked on a smart email marketing tool to figure out emails of potential clients and send customized emails which has helped us get 5 clients in the last month. Both these products have been made in the last 2 months
Till last interview, we were building a marketplace to sign up experts and fulfil requests by searching from our pool. However we realised it will take very long to be useful, and we can achieve better results by leveraging online databases and instead should focus on automated expert search and aggressively growing revenue
We also have a new technical cofounder on board who has built this expert search engine.
This idea solves a personal pain point I (Aditya) experienced during my consulting and industry experience. I have needed to engage consultants who can advise me on industry/market or work on a problem I am facing in my role (e.g sentiment analysis of customer reviews on Flipkart). Inevitably I had to turn to outside experts but on-boarding them as vendors for short-term assignments was a big pain
We have direct domain expertise due to our consulting and research background which has helped us to fulfil more than 1000 consulting hours. We have translated this experience to build an expert search engine being implemented by Ramkesh who has wide technical experience in building intelligent systems.
Many companies are turning to gig economy to accomplish work requiring specialized skills. Eg. GE has partnered with Upwork, E&Y and PWC have built their own platforms to hire contract high-skilled staff. Several companies are also catering to this demand and seeing robust growth like Expert360, Catalant, Toptal, Gigster. At the same time, there is an explosion of white-collar free-lance consultants globally (estd > 4 Mn) as well as working professionals who are looking to get good side income through gigs
A completely automated system to understand client requests for expertise, search and onboard experts and fulfil client requests. Complete automation transforms the economics of the business as it enables us to handle large number of requests with very little manpower. This allows us to price our experts very affordably thus opening up doors to both poach existing users and acquire many new clients who can afford the service
Current substitutes for expert consultations are
Consulting/PE/Finance companies use expert networks like GLG or social networks like linkedin/facebook
Some large companies use expert networks while most of them use their social networks or startups like Catalant, Expert360
Three types of organized competitors in addition to personal networks that people tap into for expert consultations
1. GLG/Other expert networks — Can get experts anywhere, however most are strong per industry or geography. Very expensive at $1000/hr
2. Business talent startups like Catalant, Expert360, — Limited by geography or functional area/industry with option of searching only among profiles listed. E.g. Both these companies usually caters to general management consultancy.
3. Companies mostly focussed on tech freelancing like Upwork, Toptal, Gigster
We fear business talent startups the most because they understand this industry well. Toptal is also a strong potential player as they have ventured into financial consulting with acquisition of SkillBridge
To hire industry experts for gigs, clients mainly look for 2 things — (1) Track record of solving similar problems, (2) Price. Competing companies do not optimize for both. Expert networks like GLG are able to find the best fit experts but have a manual process which makes it super expensive.
Marketplaces optimize for price but usually do not have the right experts as their pool is restricted. If a wide variety of expertise requests cannot be satisfied, clients will start looking for alternatives.
AI & tools have made it possible to simulate expert network services with the pricing of marketplaces. We plan to exploit this
(We realize you can’t know precisely, but give your best estimate.)
Market for industry expert gigs ~USD 25 Bn of which expert calls are $2 Bn and longer consultations ~$23 Bn.
Expert calls is a well defined market of which GLG has more than 20% market share. Consulting firms make up one-third of the market, corporates and PE firms another one-third and the rest are financial institutions, small and medium firms.
For longer consultations, US is ~55% of global organized market. There are 2.5 mn expert freelancers in US out of which we estimate 8% earn more than $20000 per annum from gigs (US Income tax data). Surveys (e.g. Bloomberg) give higher estimate of 3.2 mn workers earning 6 figure income through gigs, however income tax data is a better indicator. The above gives around $14Bn for the US market and the rest is made up by global consultations
We believe our automated searching, ability to cater globally and presence with MNCs puts us in a highly advantageous position to attack both these segments. At the very least, we should capture a significant share of the 2 Bn USD expert calls market with focussed outreach. Our gross profit is ~38% and we have enough room to reduce prices as we scale with technology.
Three pronged distribution strategy
1. Approach all employees of bulk users like consulting/PE firms — They are empowered to onboard a new expert providers
2. Approach all ex-consultants of top tier consulting firms — Around one hundred thousand of them in 10000 firms globally. They can relate to this concept and appreciate the value of experts — also are in senior positions to make decisions
3. Approach top management of corporates — Tell them about how we can help with current issues. E.g. Electric vehicle tech for automobile manufacturers
We have implemented first two strategies by building a lead generation and emailing system which scraps profiles, figures out email address and emails automatically
Third one, we are building an intelligent tool to identify top of mind issues for client/industry through web scrapping and using AI APIs to filter out top industry topics. These issues will be highlighted in the emails we send to them
We are not worried about supply of experts as we are leveraging existing databases
Ramkesh writes the code and anchores the technical backend and frontend. Aditya has automated the business development engine through python. Some of the website code was written by a freelancer, but we have secured letters saying the code belongs to Vedak
Hacker-rank for business professionals. There is a growing demand for generic skills like structuring, analytics etc at middle-management levels in all companies. However in absence of good screening tests to test these skills, companies have to filter from top schools and conduct interviews which is very expensive. Building a hacker-rank for business professionals can help in democratizing access to these coveted middle-management jobs.
These tests will have to be adaptive and mirror the case approach used by consulting firms which are the best way to test structuring and analytic skills
Our interview experience was fairly subdued with main questions coming from Jared Friedman (Founder of Scribd) and Adora Cheung (Founder of Homejoy).
Questions were on similar lines to last time
- Tell us about clients, how do they use the service
- How do you find new clients (distribution)
- Some questions on the internal tool we had built to quickly find experts on Linkedin — how much time it usually takes to search, won’t linkedin stop you at some time from scraping etc
- What is the most impressive example of a consulting assignment you delivered
- Some questions on business metrics
Looking back, it was mainly the lack of understanding of numbers that did us in, the numbers were difficult to come by mainly because it was still operating as an adhoc consulting service. As is evident, we were not selected and got the following mail
Unfortunately, we’ve decided not to fund Vedak.
We’re pretty excited about the large opportunity in connecting companies to experts in India, and we liked the way you’re bootstrapping the supply side of the business by scraping experts on Linkedin. However, what gave us pause is that we didn’t believe in the defensibility of this method. In particular, you mentioned that by making it much more low cost, you can charge less to clients. But we’re a little afraid that by playing the low-cost game, it becomes a long way down to the bottom in terms of quality and margins. We would’ve love to hear more on why your experts were better instead and thus providing a better service.
That said, this was a hard decision for us because you’re clearly smart founders. It may be that we’re wrong and if so, we hope you prove us so. I’d be happy to keep in touch and hear about your progress.