While Being Highly Profitable, I Help Deep Tech Entrepreneurs Go From Zero to $1M+ in 12 Months without or in spite of Fundraising...

...By Leveraging The Power of Sales Letters Wireframes, Technical Pre-Selling, and 
No-Code/Low-Code Outbound Prospecting 

Click "Get A Price" to introduce yourself.
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(All call to actions are congruent and link to the /quiz or /questionnaire page)
(Hero Video or Video Sales Letter (Niche Specific) You can include multiple video sales letters on this page. Just stack them on top of each other). 
Case Studies
Parabots €10k To €730k In 14 Months
Parabots - Page Rating Bot Services - provides services in text mining and information extraction, web search and web monitoring. Among its customers are 8 government agencies with concerns in fiscal and security implications from web activities. Their flaghip product - Xbots - illustrates the far reaching possibilities of web collection technology.
The Process
Introduced improvement to sales, deployment, and project management processes to this post-PMF b2b product, including close-loop feedback on the custom features development. Masterminded and created assets/materials for top, middle, bottom of the marketing funnel and for the training 100+ tax inspectors for total of 40+ workshop-days. Supported two software developers in the full product lifecycle, integrating customer feedback into product requirements, driving prioritization and pre/post-launch execution.
The Results
Parabots collected €730k+ of cash in 14 months (vs. €10-20k p.a. in the past five years) for their existing product Xbots for five on-site deployments to their clients. The profit margins went from -100% to 500%. One of their clients was so happy with Parabots that they re-engaged 5 times (this never happened before). Parabots received perfect NPS two times from ca. 50 end-users each time (this also never happened before). Parabots noticed an opportunity and also niched out with two more offerings around their product (strategic analyses and implementation of 3rd party software). Their team grew from one to four. Their end-user base grew from 3 to 70+ end-users. 
Parabots
Niche: Artificial Intelligence
Result: €10k to €730k in 14 Months
CTO: George Solakidis
Thesis: "Web crawling and text mining"
MSc: Software Engineering
Startup 1
Niche: Artificial Intelligence
Result: €10k to €730k in 14 Months
Chief Technology Officer (CTO)
Thesis: "Web crawling and text mining"
MSc: Software Engineering
Startup 1 €10k To €730k In 14 Months
Startup 1 - provides services in text mining and information extraction, web search and web monitoring. Among its customers are 8 government agencies with concerns in fiscal and security implications from web activities. Their flagship product - A - illustrates the far-reaching possibilities of web collection technology.
The Process
I introduced improvement to sales, deployment, and project management processes to this post-PMF b2b product, including closed-loop feedback on the custom features development. I masterminded and created assets/materials for the top, middle, bottom of the marketing funnel and for the delivery of the software. I supported two software developers in the full product lifecycle, integrating customer feedback into product requirements, driving prioritization and pre/post-launch execution.
The Results
For Startup 1, I collected €730k+ of cash in 14 months (vs. €10-20k p.a. in the past five years) for their existing product A for five on-site deployments to their clients. The profit margins went from -100% to 500%. One of their clients was so happy with Parabots that they re-engaged them 5 times (this has never happened before). Parabots received perfect NPS two times from ca. 50 end-users each time (this also never happened before). Startup 1 noticed an opportunity and also niched out with two more offerings around their product (strategic analyses and implementation of 3rd party software). Their team grew from one to four. Their end-user base grew from 3 to 70+ end-users. 
Startup 2
Niche: Machine Learning
Result: From Idea to €170k in 12 Months
Chief Technology Officer (CTO)
Startup 2 From Idea To €170k In 12 Months
Startup 2 delivers Product A datamining software suite and provides services in the development of dedicated business intelligence and predictive analytics applications. Startup 2 is a specialist in forensic and spatio-temporal data mining and police forces are among its main customers. Startup 2 wanted to diversify and expand their predictive analytics software into the e-commerce niche.
The Process
I designed and implemented automated marketing and sales funnel for data science / machine learning consultancy projects for their new Product B in e-commerce space: crafted sales letter and transposed to videos and then to the landing pages, quizzes, custom code, outbound sequences, and slide deck, and sales scripts and integrated all funnel steps into Clickfunnels, calendar, CRM, Gmail, and Zoom, incorporated data, market and performed product audits – in Jira, GitLab, SQL, and Python code - to inform product roadmaps and feature prioritization. I also pre-sold and delivered clustering projects, A.I. recommender systems, and sold, designed and delivered a production-ready A.I. solution for a producer of fertilizer granules.
The Results
This pre-PMF b2b data science product B in e-commerce grew from €0 to €170k in sales in 12 months. Startup 2 signed up six new clients. Startup 2's new e-commerce product B found a customer avatar in business selling online with between €20m-€500m in revenues, where Startup B can identify potential loss/gain on their clients' e-commerce sales data, with such results as €3.42m for a specialized work-clothing firm, €10m for outdoor business, or €25m for a high-end department store.
Startup 3
Niche: Artificial Intelligence
Result: €1M to €2M in 14 Months
Chief Executive Officer 
(CEO)
Thesis: "Agent-based neural networks"
MSc: Artificial Intelligence
Startup 3 €1M To €2M In 14 Months
Startup 3 - consists of four companies active in different AI application areas. The group counts 20+ AI specialists with backgrounds in AI, mathematics, informatics, robotics, software engineering and psychology.
The Process
I improved multiple products, sales and deployment processes by working with 25 STEM-degree staff across cross-functional teams of engineers, designers, data scientists, and researchers on Startup 3's own products.
The Results
Startup 3 grew 100% and invoiced an additional €1m in 14 months while increasing revenues to €1m and profit margins from 5% to 26% (vs. 7 years of 0% growth). The cash balance went from €50k to €1.1M. This allowed for healthy investment in staff, tools, office, and stable future growth.
Startup 4
Niche: Computer Vision SaaS
Result: From Idea to 1'000 Users
Chief Technology Officer (CTO)
Thesis: "A model-based method for automatic facial expression recognition"
MSc: Artificial Intelligence
Startup 4 From Idea to 1'000 Users
Startup 4 provides cloud-based services for human emotion and behavior analysis. Its first service Product (A) is now available. Product A allows companies and scientists to effectively perform online marketing or scientific research.
The Process
Together with the team, and brought in an external growth consultant, I audited and reviewed automated marketing and sales funnel (including sales letter, landing page, custom codes, outbound sequences, slide deck, and integrated all funnel steps, incorporated data, market and performed product audits. I wrote and had peer-reviewed technical assets (white papers, validation studies).
The Results
This pre-PMF b2b product, Product A, went from an idea to 1000+ users, with brands - such as Ipsos, Panteia, Intage, Kaspersky Lab, Microsoft, AB InBev, Accenture, Stanford University, University of Oxford, Harvard University - using it to conduct their neuro-marketing studies.

Product A website now features multiple technical assets: internal and external validation studies, case studies, and blog posts, which are used in inbound and outbound marketing, sales scripts, and in ads.

Startup 5
Niche: Computer Vision 
Result: From Idea to €140k in 60 Days
Founder
PhD: Psychology
Thesis: "The effects of direct current stimulation and cognitive bias modification"
Startup 5 From Idea To €140k In 60 Days
Startup 5's Product is a ground-breaking high-tech IT system for tracking eye movements using a simple webcam. Startup 5's product enables the world’s most advanced solutions to measure the experience of someone using a laptop, tablet or smartphone.
The Process
I masterminded and wrote the entire sales arguments/letter for Product A and helped the team behind Startup 5 to write the roadmap for the Product A. I personally attained the first €140k in revenues for this Product A.
The Results
This pre-PMF b2b webcam-based eye-tracking Product A, of Startup 5, went from Idea to €140k in revenues and 80% cash collected in 8 weeks. The Product A was taken over and integrated as a key feature into a Product B- a SaaS platform.

Startup 6
Niche: Computer Vision
Result: From Idea to €50k in 30 Days
Founder
Thesis:  "Semantic features  recognition in faces using deep learning"
PhD: Artificial Intelligence
Startup 6 From Idea To €50k In 30 Days
Startup 6 is a Product A's feature based on remote photoplethysmography, which detects heart rate (in BPMs) and heart rate variability (RMSSD and SDNN) remotely and unobtrusively through an HD webcam.
The Process
I masterminded and wrote the entire sales arguments for Product A and helped the team behind the Startup 6 to write the roadmap for the Product A. I personally attained the first €50k in revenues for this Product A.
The Results
This pre-PMF b2b product, Startup 6, went from an idea (0€) to €50k in 30 days. The Product A was taken over and merged into a computer vision suite of products.

Startup 7
Niche: Computer Vision
Result: From Idea to €15k in 6 months
Product Founder
Thesis: "Active appearance models for gaze estimation"
MSc: Business Informatics
Startup 7 From €0 to €15k in 6 months
Startup 7's Product A SDK and API for developers easily integrates facial expres­sion analysis into other applications. The SDK is available for Windows and Android, and can run on PC or server. 
The Process
I prepared marketing and sales assets and arguments, including qualification questions, landing page, and pricing, and trained ca. 20 salespeople on the correct sales language patterns and objections handling leveraging how we went and sold the first Startup 7's SDK clients ever from the inbound leads. I created the niche targeting and the customers' avatar off the dozens of customer development and discovery calls taken. I also reviewed technical guidelines and contributed to the product roadmap.
The Results
This pre-PMF b2b product, Startup 7, went from an idea (0€) to €15k cash collected in 6 months. The sales and marketing team behind the Product A SDK has now focused on delivering results for their clients whilst using my technical assets, landing pages and proven scripts to continue to bring SDK leads for their business.
Startup 8
Niche: SaaS and Tech startups
Result: From $4M to $13M in 12 months
Founder
Thesis: "Lasers and quantum mechanics"
BSc: Engineering Physics
Startup 8 From $4M to $13M in 12 months
Startup 8 helps SaaS and online service businesses scale to $10M in record speeds, all while being extremely capital efficient. Some of the startups helped are backed by incubators and firms like Y-Combinator, 500 Startups, TechStars, Sequoia Capital, Social Capital. Case studies: AdvisorStream ($0-$1M 12 Months. $1M-$5M 24 Months. Sold To Broadridge); CoPilot Advisor ($0-$1M 11 Months); Seamless.ai ($200k-$3.5M 11 Months); Press Advantage ($0-$1M 12 Months); Lead Engine Pro ($0-$1M 4 Months); Keboola ($3M-$6M 10 Months); Kinobody ($2M-$12M 24 Months); Effct.org ($360k-$1.7M 4 Months); Hubbli ($360k-$1M 12 Months) and 2000+ SaaS and Online Service-based Businesses
The Process
I prepared and implemented sales and marketing automatization tools & admin -user management, maintenance, entry creation, review, data analysis, KPI monitoring- for ca. 40 tools. I tested and audited multiple processes (support calls, clients’ referrals, clients’ onboarding sales attribution, sales pipeline, ensuring that reps are following the sales and marketing playbook, identifying non-compliance). I contributed to the product and customer success teams (created or reviewed, i.a.: slide decks, operational and financial models & valuation; ads ideation, new platform features, [video] sales letters). I sourced 4k+ and sent 10k+ messages to outbound leads and performed 50+ outbound strategy calls.
The Results
The revenue grew from $350k to $1.1m p.m. ($13m p.a), the sales team expanded from 40 to 80 SDRs, AEs, CS, the referral/affiliate partnerships went from 19 to 37, and the app users went from 2.5k to 3.8k.
Financial Institution 1
Niche: Machine Learning
Result: From Idea to Product in 4 months
Financial Institution Idea to Product in 4 months
Together with this financial institution, I identified that their business needed machine learning systems and processes to give more clarity on the credit risk of their customers in the digital channels. Once I narrowed down the options, I then built and productized together regulation-compliant machine learning models (Python, SAS, Hadoop, Xgboost, random forest), new data sources and model optimizations (self-learning) which decreased credit loss while rejected fewer clients and earned an extra profit in that b2c channel (vs. benchmark).
Fintech 1
Niche: Machine Learning
Result: From 2 to 12 demos/week in 45 days
Fintech From 2 to 12 demo calls per week in 45 days
After a couple of meetings, I identified that this b2b2c fintech needed systems and processes to give them more clarity on who their ideal clients are, giving them the ability to consistently book demos. This fintech went from 2 to 12 demonstration (demo) calls per week in 45 days booked with qualified enterprise b2b leads.
(Before state)

"Before engaging with {your company}, we were {previous state}. Our metrics were {insert previous state metrics}."  

After state

"We started working with {your company}. The results were great: {Insert after state feelings, metrics, etc.}"

 - [Client Name], [Client Position], [Client LinkedIn], [Date]
(money shot - example of your client getting results - screenshot, charts, before/after metrics, etc..)
(customer testimonial video)
(client headshot)
[Client Name] 
[Client Position] 
[Client LinkedIn]
(client logo)

Peter Lewinski

10
companies
helped build
12
deep tech product
helped scale-up
€1M
sold personally
in 12 months of deep tech products

1x founder

deep tech startup
computer vision

1100x+

cited
Cumulative IF: 33.5
Reviewed: 36, 
edited: 9 papers
phd & 
post-doc & professor
& U. of Oxford MSc
& U. of Amsterdam PhD
& Chicago Booth EMBA

Growth Consulting - My Story:

Hi, I am dr. Peter Lewinski and I aspire to be in top 1% in growth consulting. 

I am an experienced growth consultant - focused on four elements -marketing automation, -sales operations, -product management, and -operations for: tech, A.I., data science/ML, fintech, banking, and sales/consulting verticals. 

I scaled up 7 SMEs, 1 bank, 3 non-profit associations, co-founded 1 startup, and was employed in 5 universities.

I scaled up an A.I. startup from €1M to €2M in 14 months which did not grow for 5 years prior. 

I grew revenues and user-base for 10+ products from anywhere of 0, £100k-£500k, £2M to £10M for startups and helped a bank enable billions in loan portfolio growth. 

I became a director in a very technical field – credit risk modeling - in the top corporate - without prior IT & programming skills while at the same time making a tenure-track assistant professor in neuro-marketing in the top 45 FT-Ranking business school, both by age 26.

I taught 5 full bachelor's and master's courses in marketing, neuro-marketing, and strategy to 100s of university students. 

I reviewed 36 journal papers, edited 9 papers, and co-edited 1 special issue, and presented in 24 academic conferences in 3 years. 

My 12 journal publications feature a cumulative impact factor: 33.49 per Clarivate, JCR, and all 20 of them were cited 1100+ times as per Google Scholar. 

My publications are top 2 & top 5 most cited and all of them (20) account for 60% of all the citations in my scientific niche out of 1000s publications in Google Scholar.

I did eight university degrees: two Bachelors, four Masters, Ph.D., Postdoc, Assistant Professor, and Executive MBA in 4 different languages (English, Spanish, Dutch, Polish) in 6 different fields from the top UK, USA, and EU universities (Oxford, Chicago Booth) by age 31 across 6 different countries while always working full time. 

I did three different 5-year long degrees – equivalent to 900 ECTS - in 2.5 years each. I am on the way to finishing 100+ courses across 20 universities. 

I finished my Ph.D. and started my Postdoc by age 25 and graduated with 10 publications (3x times the norm) in top quartile journals (Clarivate) in the top 1 (QS World Ranking) marketing department while working full-time in an A.I. firm, leading 6 interns in 3 years and pursuing 2nd bachelor’s degree.

I have a black belt (1st Dan) in Judo and I participated in 200+ inter(national) judo competitions/tournaments and twice became a National Judo Team Vice-Champion. I was on the Oxford University Judo Club (winning team member of the Varsity Match with Cambridge University) and on Oxford Lincoln College Boat Club (Rower M4), and I qualified for U.S. State Finals (Oregon) in 4x400 Relay.

How It Works

(In this section, you are answering the question "How do you do it?". This can be thought of as the "feature section". In this section, you want to explain each feature in the context of the benefit - meaning how can the prospect use the feature to achieve a benefit? Instead of throwing features and technical information at the prospect, walk them through the "jobs that they can do better, faster, easier, cheaper" by comparing the old way against the new way. Use a screen share and voice-over in this section and write out the feature copy beside the video. Make sure videos are large enough such that the prospect can understand what you are showing them! You can also include quotes beside each feature - experts from customers praising the feature.)
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