Information 
  about 
  Tellspec 
  Inc. 
  
Q&A 
  Confidential 
   
  

 
  
 
  
 
  
Company 
  Profile 
  
 
  
 
  
Basic 
  Information 
  
Company 
  Name 
   Tellspec 
  Inc 
  
Contact 
  Name 
  
Isabel 
  Hoffmann 
  (Isabel@tellspec.com) 
  
Company 
  Website 
  
www.tellspec.com 
  
URL 
  5-­‐minute 
  video 
   
  
https://www.youtube.com/watch?v=i3a4P7NyJkU 
  

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Sector 
  (mark 
  only 
  one) 
  
Big 
  Data 
  
Digital 
  Health 
  
Mobile 
  Health 
  
Bio 
  & 
  Life 
  Sciences 
  
BioTech 
  
IT 
  -­‐ 
  Hardware 
  
IT 
  -­‐ 
  Software 
  

 
  

Other 
  profile 
  questions 
  
Affiliated 
  university, 
  accelerator 
  and/or 
  incubator, 
  if 
  any: 
  

AZ 
  TechCelerator, 
  Surprise, 
  Arizona; 
  Manchester 
  Univ, 
  UK 
  

Legal 
  form 
  of 
  company? 
  (e.g. 
  C-­‐corp., 
  S-­‐corp., 
  LLC, 
  Partnership) 
  

C-­‐Corp 
  

Intellectual 
  property 
  protection, 
  if 
  any 
  

Patent 
  and 
  name 
  trademark 
  

 
  
 
  
Question 
  1: 
  What 
  is 
  your 
  “Elevator” 
  Introduction? 
  
Brief 
  elevator 
  pitch 
  for 
  your 
  company 
  
Tellspec 
  Inc. 
  is 
  digital 
  health 
  company 
  that 
  provides 
  predictive 
  intelligence 
  about 
  food, 
  by 
  combining 
  NIR 
  spectroscopy, 
  bio-­‐
informatics 
  techniques 
  & 
  deep 
  learning 
  algorithms 
  in 
  a 
  revolutionary 
  technology 
  that 
  analyzes 
  consumer 
  foods 
  at 
  the 
  molecular 
  
level. 
   
  
Tellspec’s 
  mission 
  is 
  to 
  help 
  create 
  a 
  clean 
  food 
  revolution 
  by 
  providing 
  consumers 
  with 
  information 
  about 
  what 
  is 
  really 
  in 
  their 
  
food 
  beyond 
  the 
  nutrition 
  label. 
  As 
  the 
  world’s 
  first 
  consumer 
  food 
  sensor, 
  Tellspec 
  identifies 
  calories, 
  macronutrients, 
  ingredients 
  
and 
  allergens 
  in 
  foods 
  as 
  well 
  as 
  specific 
  nutritional 
  information 
  such 
  as 
  glycemic 
  index. 
  Our 
  three-­‐part 
  system 
  includes 
  a 
  pocket-­‐
sized 
  scanner, 
  a 
  cloud-­‐based 
  analysis 
  engine 
  and 
  a 
  mobile 
  app 
  that 
  work 
  together 
  to 
  scan 
  foods, 
  identify 
  ingredients 
  and 
  provide 
  
details 
  on 
  what 
  these 
  ingredients. 
   
   
  
 
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
  
Question 
  2: 
  -­‐ 
  -­‐Market 
  & 
  Industry 
  Analysis 
  
How 
  large 
  is 
  your 
  market? 
  What 
  market 
  segments 
  are 
  you 
  going 
  after 
  and 
  why? 
   
  
TellSpec’s 
  food 
  sensor 
  enables 
  those 
  that 
  who 
  desire 
  weight 
  loss 
  to 
  automatically 
  track 
  their 
  calories 
  and 
  identify 
  food 
  sensitivities 
  
by 
  simply 
  scanning 
  their 
  food. 
  TellSpec’s 
  food 
  sensor 
  also 
  helps 
  diabetic 
  or 
  pre-­‐diabetic 
  patients 
  to 
  analyze 
  their 
  diet, 
  and 
  in 
  
particular 
  count 
  calories 
  and 
  carbohydrates, 
  so 
  they 
  can 
  adjust 
  their 
  insulin 
  doses 
  accordingly. 
  Tellspec 
  app 
  also 
  helps 
  track 
  the 
  total 
  
intake 
  of 
  macronutrients 
  and 
  allergens 
  per 
  meal, 
  per 
  day 
  as 
  well 
  as 
  for 
  the 
  month. 
  
 
  
Is 
  this 
  market 
  growing? 
  How 
  fast? 
   
  
Global 
  diabetes 
  market 
  is 
  expected 
  to 
  reach 
  $44.70 
  billion 
  in 
  2015, 
  compound 
  annual 
  growth 
  rate 
  (CAGR) 
  of 
  7.5%. 
  The 
  WHO 
  projects 
  
the 
  world’s 
  diabetic 
  population: 
  366 
  million 
  by 
  2030. 
  The 
  market 
  for 
  food 
  allergy 
  and 
  intolerance 
  is 
  estimated 
  by 
  Global 
  Industry 
  
Analysts 
  to 
  be 
  US$26.5bn 
  by 
  2017. 
  This 
  market 
  has 
  grown 
  at 
  18.5% 
  over 
  the 
  past 
  decade. 
  
 
  
Who 
  is 
  in 
  the 
  market 
  already? 
  What 
  is 
  the 
  nature 
  of 
  competition 
  – 
  direction, 
  indirect, 
  substitutes? 
  
Several 
  apps 
  target 
  the 
  weight 
  loss 
  industry 
  by 
  offering 
  ways 
  to 
  count 
  calories, 
  some 
  even 
  count 
  macronutrients, 
  but 
  none 
  can 
  
detect 
  allergens 
  that 
  a 
  user 
  may 
  react 
  to, 
  because 
  no 
  app 
  can 
  scan, 
  at 
  the 
  molecular 
  level, 
  the 
  actual 
  food. 
  Many 
  medical 
  devices 
  
help 
  diabetic 
  people 
  manage 
  their 
  blood 
  sugar 
  ranging 
  from 
  glucose 
  meters 
  to 
  pumps, 
  but 
  none 
  connect 
  this 
  information 
  to 
  the 
  
food 
  that 
  the 
  patient 
  eats, 
  so 
  they 
  are 
  not 
  direct 
  competitors 
  but 
  possible 
  collaborators 
  in 
  data 
  integration. 
  
 
  

 
  

 Question 
  3: 
  Go-­‐to-­‐Market 
  Plan 
  
Who 
  are 
   
  your 
  customers? 
  Describe 
  your 
  engagement 
  with 
  them 
  to 
  date. 
   
  
Primary 
  customer: 
  diabetic, 
  pre-­‐diabetic, 
  or 
  an 
  allergy 
  sensitive 
  patient. 
  Secondary 
  customer 
  a 
  person 
  that 
  want 
  to 
  lose 
  weight 
  or 
  a 
  
person 
  that 
  is 
  following 
  a 
  fitness 
  program 
  and 
  need 
  to 
  track 
  calories, 
  macronutrients 
  and 
  allergens. 
   
  
On 
  September 
  3rd, 
  Tellspec 
  is 
  participating 
  in 
  an 
  event 
  for 
  diabetic 
  people, 
  organized 
  by 
  Orange 
  Telecom. 
  The 
  event 
  is 
  called 
  
mHealth 
  Grand 
  Tour 
  2015 
  http://www.mhealthtour.com/2015 
  and 
  it 
  will 
  give 
  riders 
  the 
  chance 
  to 
  cover 
  1,500 
  km 
  by 
  bicycle, 
  from 
  
Brussels 
  to 
  Geneva 
  via 
  some 
  of 
  the 
  most 
  beautiful 
  parts 
  of 
  France. 
  This 
  Tour 
  brought 
  together 
  around 
  54 
  cycling 
  enthusiasts 
  
diagnosed 
  with 
  type 
  1 
  or 
  type 
  2 
  diabetes, 
  fitted 
  with 
  kit 
  from 
  the 
  partners 
  that 
  will 
  enable 
  monitoring 
  of 
  their 
  physical 
  condition 
  and 
  
personalized 
  coaching 
  from 
  the 
  Tour’s 
  medical 
  team. 
  Tellspec 
  has 
  offered 
  during 
  the 
  tour, 
  our 
  first 
  food 
  sensor 
  which 
  will 
  allow 
  the 
  
diabetic 
  riders 
  to 
  analyze 
  their 
  diet, 
  and 
  in 
  particular 
  count 
  calories, 
  carbohydrates, 
  proteins, 
  fats, 
  sugar 
  as 
  well 
  as 
  the 
  glycemic 
  index 
  
of 
  each 
  food 
  consumed. 
  After 
  scanning 
  their 
  food 
  and 
  receiving 
  via 
  a 
  mobile 
  app 
  the 
  results, 
  riders 
  can 
  then 
  adjust 
  their 
  insulin 
  dose 
  
accordingly, 
  and 
  they 
  can 
  track 
  the 
  total 
  intake 
  of 
  macronutrients 
  per 
  meal, 
  per 
  day 
  as 
  well 
  as 
  for 
  the 
  duration 
  of 
  the 
  ride. 
   
  
 
  
Describe 
  how 
  you 
  win 
  customers 
  today. 
  Describe 
  your 
  future 
  customer 
  acquisition 
  strategy. 
  
A 
  significant 
  amount 
  of 
  funding 
  to 
  date 
  has 
  been 
  generated 
  from 
  on-­‐line 
  pre-­‐orders. 
  We 
  current 
  pre-­‐sell 
  our 
  food 
  scanners 
  in 
  our 
  
site; 
  social 
  media, 
  public 
  speaking 
  & 
  tradeshow 
  appearances 
  methods 
  we 
  currently 
  use. 
  Going 
  forward 
  we 
  plan 
  to: 
  implement 
  a 
  
social 
  media 
  strategy 
  partnering 
  with 
  Google 
  digital 
  strategy 
  team, 
  to 
  reach 
  a 
  large 
  qualified 
  audience 
  and 
  create 
  demand; 
  sell 
  
product 
  in 
  online 
  sites 
  – 
  Amazon, 
  Alibaba; 
  approach 
  diabetic 
  associations, 
  celiac 
  associations 
  to 
  so 
  they 
  carry 
  our 
  product; 
  partner 
  
with 
  large 
  weight 
  control 
  clinics, 
  & 
  fitness 
  organizations; 
  sell 
  product 
  directly 
  to 
  a 
  selected 
  set 
  of 
  large 
  retailers 
  (Best 
  Buy, 
  Apple); 
  El 
  
Coret 
  Ingles); 
  partner 
  with 
  wellness 
  and 
  preventive 
  clinics 
  to 
  carry 
  our 
  product; 
  develop 
  partnership 
  with 
  pharmaceutical 
  companies 
  
that 
  are 
  already 
  selling 
  medical 
  devices 
  to 
  control 
  blood 
  sugar 
  in 
  order 
  to 
  piggyback 
  on 
  their 
  distribution 
  and 
  as 
  well 
  as 
  to 
  share 
  
some 
  of 
  the 
  aggregate 
  data 
  collected. 
  
 
  
How 
  will 
  you 
  displace 
  any 
  competitors? 
  How 
  are 
  you 
  better/different 
  than 
  your 
  competitors? 
  What’s 
  your 
  channel/partnership 
  
strategy, 
  if 
  any? 
   
  
Currently 
  we 
  are 
  totally 
  unique 
  in 
  the 
  fact 
  that 
  we 
  detect 
  and 
  track 
  the 
  intake 
  of 
  not 
  just 
  calories 
  and 
  macronutrients 
  but 
  also 
  
allergens 
  and 
  potentially 
  toxic 
  by-­‐products 
  of 
  food 
  manufacturing 
  as 
  well 
  as 
  toxic 
  chemicals 
  in 
  the 
  food. 
  We 
  are 
  creating 
  
partnerships 
  with 
  the 
  large 
  pharmaceutical 
  groups 
  that 
  are 
  targeting 
  diabetics, 
  with 
  as 
  well 
  as 
  medical 
  associations, 
  clinics, 
  fitness 
  
and 
  wellness 
  organizations 
  to 
  create 
  awareness 
  and 
  traction. 
  We 
  have 
  also 
  requests 
  from 
  several 
  universities, 
  hospitals 
  and 
  clinics, 
  
(including 
  Mount 
  Sinai 
  NY 
  and 
  Centre 
  for 
  Clinical 
  Investigation 
  at 
  Harvard 
  University 
  ) 
  to 
  collaborate 
  in 
  clinical 
  trials 
  regarding 
  
nutrition, 
  obesity 
  and 
  diabetics. 
  
 
  
 
  
Question 
  4: 
  Technical 
  Product 
  Description 
  and 
  Plan 
  
Briefly 
  describe 
  your 
  product. 
   
  
We 
  offer 
  a 
  simple 
  method 
  for 
  the 
  consumer 
  to 
  know 
  what 
  is 
  in 
  their 
  food, 
  and 
  the 
  ability 
  to 
  track 
  calories, 
  macronutrients, 
  glycemic 
  
index, 
  allergens 
  and 
  other 
  food 
  concerns. 
  
 
  
Describe 
  your 
  technology. 
   
  
Tellspec’s 
  food 
  sensor 
  is 
  a 
  hand-­‐held 
  near-­‐infrared 
  (NIR) 
  spectrometer. 
  Its 
  major 
  components 
  are: 
  a 
  diffraction 
  grating 
  which 
  spreads 
  
light 
  into 
  a 
  spectrum, 
  a 
  digital 
  mirror 
  array 
  which 
  selects 
  different 
  parts 
  of 
  the 
  spectrum, 
  and 
  a 
  solid-­‐state 
  infrared 
  detector 
  which 
  
measures 
  the 
  intensity 
  of 
  the 
  light 
  at 
  the 
  selected 
  part 
  of 
  the 
  spectrum. 
  The 
  spectrum 
  is 
  then 
  processed 
  by 
  TellSpec’s 
  algorithms 
  in 
  
the 
  cloud, 
  to 
  produce 
  information 
  about 
  the 
  food 
  scanned. 
  The 
  scanning 
  process 
  involves 
  light 
  being 
  sent 
  out 
  to 
  reflect 
  off 
  of 
  the 
  
food 
  being 
  scanned. 
   
  The 
  grating 
  spreads 
  the 
  returning 
  light 
  into 
  a 
  spectrum 
  so 
  that 
  different 
  wavelengths 
  hit 
  different 
  parts 
  of 
  the 
  
digital 
  micromirror 
  device 
  (DMD). 
  Tellspec 
  has 
  a 
  partnership 
  agreement 
  with 
  Texas 
  Instrument 
  to 
  use 
  the 
  TI’s 
  DLP 
  projection 
  
technology 
  and 
  its 
  optical 
  semiconductor 
  (DMD). 
  One 
  after 
  another, 
  mirrors 
  on 
  the 
  DMD 
  are 
  moved 
  to 
  cause 
  different 
  wavelengths 
  
to 
  shine 
  on 
  the 
  detector. 
  The 
  scanner 
  records 
  the 
  intensity 
  of 
  the 
  different 
  wavelengths, 
  and 
  that 
  generates 
  a 
  unique 
  spectrum 
  or 
  
fingerprint 
  of 
  the 
  food. 
   
  
The 
  scanner 
  then 
  sends 
  this 
  fingerprint 
  that 
  it 
  collects 
  to 
  your 
  smartphone 
  and 
  the 
  phone 
  sends 
  it 
  on 
  to 
  Tellspec’s 
  servers 
  in 
  the 
  
cloud. 
  Tellspec’s 
  algorithms, 
  residing 
  in 
  the 
  cloud, 
  do 
  the 
  analysis 
  the 
  spectrum 
  for 
  information 
  about 
  the 
  food, 
  and 
  send 
  the 
  results 
  
back 
  to 
  your 
  phone 
  for 
  you 
  to 
  see. 
  
The 
  data 
  from 
  the 
  scanner 
  is 
  first 
  processed 
  to 
  put 
  it 
  into 
  a 
  standard 
  form, 
  called 
  absorbance. 
  This 
  removes 
  some 
  of 
  the 
  variation 
  
due 
  to 
  differences 
  in 
  the 
  intensity 
  of 
  the 
  light 
  source 
  and 
  the 
  wavelength-­‐dependent 
  response 
  of 
  the 
  detector. 
  The 
  absorbance 
  
spectrum 
  is 
  used 
  for 
  analysis 
  and 
  for 
  training. 
  Our 
  algorithms 
  are 
  based 
  on 
  machine 
  learning, 
  but 
  we 
  also 
  use 
  several 
  bio-­‐informatics 
  
techniques. 
  In 
  addition, 
  Tellspec 
  does 
  pre-­‐processing 
  the 
  spectral 
  data 
  in 
  light 
  of 
  known 
  principles 
  of 
  spectroscopy 
  and 
  
chemometrics 
  to 
  improve 
  the 
  algorithms' 
  accuracy 
  and 
  speed. 
  The 
  combination 
  of 
  machine 
  learning, 
  bio-­‐informatics 
  techniques 
  and 
  

 
  

 traditional 
  spectroscopy 
  gives 
  Tellspec 
  the 
  ability 
  to 
  extract 
  nutritional 
  information 
  from 
  a 
  spectrum 
  or 
  from 
  the 
  unique 
  fingerprint 
  
of 
  the 
  food 
  scanned. 
  
 
  
Technology 
  Validation. 
  (What 
  evidence 
  can 
  you 
  present 
  that 
  your 
  product 
  works 
  as 
  advertised? 
  Future 
  validation 
  plans?) 
  
We 
  currently 
  do 
  validation 
  in-­‐house, 
  and 
  have 
  written 
  validations 
  reports 
  for 
  several 
  of 
  our 
  algorithms. 
   
  We 
  have 
  line-­‐up 
  several 
  
universities 
  to 
  work 
  with 
  us 
  to 
  do 
  third 
  party 
  validation 
  studies. 
   
  
 
  
Describe 
  the 
  remaining 
  product 
  development 
  risks 
  and 
  your 
  plans 
  to 
  overcome 
  them. 
   
  
We 
  are 
  still 
  building 
  our 
  food 
  database 
  of 
  scans 
  to 
  improve 
  the 
  accuracy 
  of 
  our 
  detection; 
  the 
  height 
  of 
  our 
  current 
  beta 
  scanner 
  is 
  
still 
  going 
  to 
  be 
  reduced 
  by 
  50%; 
  and 
  not 
  all 
  models 
  for 
  food 
  detection 
  are 
  finalized. 
  We 
  are 
  currently 
  working 
  on 
  all 
  these 
  three 
  
issues, 
  and 
  with 
  respect 
  to 
  the 
  hardware, 
  we 
  continue 
  to 
  have 
  the 
  support 
  & 
  collaboration 
  of 
  Texas 
  Instruments 
  and 
  other 
  of 
  our 
  
partners. 
   
  
 
  
Describe 
  your 
  product’s 
  advantages 
  (features, 
  for 
  example) 
  for 
  end-­‐users 
  vs. 
  substitute 
  solutions 
  (not 
  just 
  direct 
  competitors). 
  
The 
  advantage 
  we 
  provide 
  is 
  that 
  our 
  user 
  can 
  detect 
  and 
  track 
  allergens 
  and 
  any 
  other 
  food 
  ingredients 
  such 
  as 
  by-­‐products 
  of 
  food 
  
manufacturing 
  or 
  contaminants, 
  which 
  may 
  be 
  of 
  concern 
  to 
  the 
  user’s 
  health. 
  We 
  also 
  offer 
  a 
  method 
  to 
  track 
  what 
  foods 
  may 
  
cause 
  food 
  sensitivities 
  by 
  offering 
  a 
  the 
  tracking 
  capability 
  on 
  how 
  the 
  user 
  feels 
  after 
  each 
  meal 
  scanned; 
  this 
  can 
  potentially 
  
replace 
  expensive 
  and 
  regular 
  allergy 
  tests. 
  
 
  
Describe 
  your 
  company’s 
  current 
  intellectual 
  property 
  status 
  and 
  plans 
  for 
  the 
  future. 
   
  
We 
  have 
  a 
  pending 
  patent 
  application, 
  and 
  several 
  trade 
  secrets. 
  Patent 
  published: 
  015-­‐02-­‐05 
  Publication 
  US20150036138. 
  Our 
  
name 
  and 
  logo 
  has 
  been 
  trademarked 
  and 
  this 
  trademark 
  is 
  now 
  registered. 
  
 
  
Discussion 
  of 
  any 
  non-­‐IP 
  barriers 
  to 
  entry 
  for 
  your 
  market. 
   
  
Our 
  IP 
  resides 
  on 
  our 
  algorithms 
  & 
  methods 
  for 
  detection. 
  We 
  have 
  patented 
  this 
  aspect 
  and 
  hope 
  to 
  be 
  awarded 
  the 
  patent 
  soon. 
  
We 
  have 
  signed 
  manufacturing 
  arrangements 
  with 
  a 
  mass 
  manufacturer 
  in 
  Taiwan 
  and 
  we 
  have 
  over 
  many 
  global 
  expressions 
  of 
  
interest 
  for 
  distribution 
  and 
  direct 
  retail. 
  We 
  have 
  signed 
  a 
  letter 
  of 
  Intent 
  with 
  Samsung 
  Electronics, 
  Seoul, 
  Korea 
  for 
  the 
  
collaboration 
  in 
  the 
  creation 
  of 
  food 
  scanners 
  embedded 
  into 
  some 
  of 
  Samsung’s 
  kitchen 
  appliances 
  with 
  the 
  use 
  of 
  Tellspec 
  
detection 
  algorithms 
  and 
  food 
  database. 
  We 
  are 
  also 
  talking 
  to 
  many 
  weight 
  control 
  clinics 
   
  and 
  gyms 
  to 
  retail 
  our 
  scanners. 
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
  
 
  
 
  
Question 
  5: 
  Economics 
  
Pricing 
  and 
  downstream 
  value 
  analysis. 
  Prove 
  there 
  is 
  a 
  compelling 
  ROI 
  for 
  end-­‐users 
  and 
  partners 
  based 
  on 
  your 
  pricing. 
   
  
Financial 
  model 
  summary 
   
  
 
  
2015 
  
2016 
  
2017 
  
2018 
  
2019 
  
Number 
  of 
  Units 
  Sold 
   
  
120 
  
20,000 
  
150,000 
  
350,000 
  
500,000 
  
Avg. 
  selling 
  price 
  
390 
  
612 
  
518 
  
418 
  
337 
  
Gross 
  margin 
  % 
  
 
  
60% 
  
60% 
  
60% 
  
60% 
  
 
   
  Below 
  in 
  ($000s) 
    
  
 
  
 
  
 
  
 
  
Revenues 
  
$47 
  
$12,247 
  
$79,003 
  
$173,371 
  
$209,339 
  
EBITDA 
  
$-­‐2,249 
  
$-­‐5194 
  
$2,131 
  
$33,925 
  
$48,696 
  
Cash 
  burned 
  / 
  created 
   
  
$-­‐2039 
  
$10,876 
  
$76,873 
  
$139,445 
  
$160,643 
  
Funding 
  required 
  
 
  
 
   
   
   
   
  $7, 
  934 
  
 
  
 
  
 
  
Note 
  – 
  Dollar 
  amounts 
  in 
  the 
  Financial 
  Model 
  Summary 
  above 
  is 
  in 
  thousands. 
   
  
 
  
 
  
 
  
Question 
  6: 
  Risk 
  vs. 
  Talent 
  Narrative 
  
What 
  risks 
  has 
  your 
  team 
  mitigated 
  so 
  far 
  (business-­‐related 
  and 
  technical 
  as 
  it 
  relates 
  to 
  your 
  business)? 
  What 
  are 
  the 
  next 
  few 
  
major 
  risk-­‐reduction 
  milestones? 
  
Mitigated 
  the 
  risk 
  of 
  using 
  different 
  spectrometers 
  from 
  different 
  brands 
  to 
  test 
  algorithms, 
  our 
  algorithms 
  are 
  now 
  “hardware 
  
agnostic”. 
  Have 
  reduced 
  actual 
  spectrometer 
  size, 
  made 
  portable, 
  wireless 
  and 
  blue-­‐tooth 
  enable. 
  Have 
  built 
  an 
  initial 
  but 
  consistent 
  
and 
  accurate 
  food 
  database. 
  Next 
  challenge 
  “temperature” 
  of 
  the 
  sample 
  & 
  sample 
  shape 
  are 
  our 
  next 
  milestone 
  for 
  algorithm 
  
deployment. 
  Finally, 
  we 
  intend 
  to 
  build 
  algorithms 
  for 
  volume 
  recognition 
  so 
  the 
  user 
  does 
  not 
  have 
  to 
  enter 
  the 
  actual 
  volume 
  
consumed. 
  For 
  this 
  R&D 
  project 
  we 
  are 
  in 
  discussions 
  with 
  several 
  universities 
  for 
  collaboration. 
   
   
   
   
   
   
   
  
 
  
 
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
  

 
  

 KEY 
  EMPLOYEES 
  
Isabel 
  Hoffmann, 
  CEO, 
  experienced 
  executive 
  leadership, 
  founded 
  eight 
  companies 
  in 
  preventive 
  medicine, 
  genetics, 
  technology, 
  in 
  
North 
  America 
  & 
  Europe. 
  Negotiated 
  large 
  strategic 
  investments 
  & 
  raised 
  equity 
  investment 
  & 
  convertible 
  debenture 
  notes. 
  
Strategic 
  negotiator 
  on 
  several 
  business 
  acquisitions, 
  including 
  US$28M 
  acquisition 
  of 
  Corel 
  Multimedia 
  business 
  division. 
  Many 
  
awards 
  including 
  E&Y’s 
  Entrepreneur 
  of 
  the 
  Year 
  (Canada) 
  MacLean’s 
  Honor 
  Role 
  Canadian 
  Business 
  Excellence. 
   
   
  
Jason 
  Vincent, 
  VP 
  Technology 
  and 
  Operations, 
  since 
  joining 
  Tellspec, 
  I 
  have 
  been 
  working 
  closely 
  with 
  the 
  technology 
  and 
  
engineering 
  teams 
  on 
  ensuring 
  milestones 
  are 
  met 
  for 
  the 
  delivery 
  targets, 
  and 
  exploring 
  commercial 
  opportunities 
  in 
  the 
  European 
  
territory. 
  
Dr. 
  Pablo 
  Carbonell, 
  Chief 
  Scientists, 
  researcher, 
  16 
  years 
  in 
  bioinformatics, 
  PhD 
  Computer, 
   
  ControlEngineering 
  (Polytechnic 
  
University 
  of 
  Valencia, 
  1999), 
  post-­‐doctoral 
  from 
  NYU 
  Polytechnic 
  School 
  of 
  Engineering, 
  where 
  he 
  worked 
  on 
  the 
  development 
  of 
  
theoretical 
  models 
  for 
  bio-­‐inspired 
  systems. 
  He 
  has 
  been 
  PI 
  or 
  scientific 
  partner 
  in 
  at 
  least 
  13 
  projects. 
   
  
Jason 
  Coulls, 
  VP 
  Software, 
  is 
  a 
  software 
  engineer 
  who 
  has 
  worked 
  in 
  the 
  mobile 
  space 
  since 
  it’s 
  inception 
  in 
  the 
  late 
  1990’s, 
  having 
  
progressed 
  through 
  Palm 
  OS, 
  Blackberry, 
  Windows 
  CE, 
  Windows 
  Mobile, 
  and 
  now 
  iOS. 
   
  He 
  has 
  worked 
  on 
  many 
  projects 
  for 
  very 
  
high 
  profile 
  customers 
  that 
  required 
  the 
  utmost 
  trust, 
  including 
  national 
  government 
  agencies, 
  law 
  enforcement 
  and 
  national 
  banks, 
  
his 
  biggest 
  contribution 
  to 
  consumer 
  mobile 
  software 
  comes 
  working 
  on 
  Clear 
  Channel’s 
  iHeartRadio 
  product 
  (now 
  called 
  
iHeartMedia) 
  supporting 
  over 
  4+ 
  million 
  users. 
   
   
  
Gail 
  Gannon, 
  VP 
  Strategy, 
   
  is 
  a 
  seasoned 
  healthcare 
  industry 
  entrepreneur, 
  well 
  connected 
  to 
  KOLs 
  in 
  private 
  and 
  public 
  sectors. 
  
Strong 
  reputation 
  for 
  conducting 
  due 
  diligence 
  and 
  negotiating 
  agreements 
  with 
  entities 
  ranging 
  from 
  start-­‐ups 
  to 
  Fortune 
  500 
  
companies 
  to 
  global 
  health 
  agencies, 
  e.g. 
  OneWorld 
  Health-­‐PATH, 
  Gates 
  Foundation. 
  
Mark 
  Bloore, 
  Senior 
  Software 
  Architect, 
  has 
  over 
  20+years 
  of 
  experience 
  in 
  software 
  design 
  and 
  development 
  in 
  many 
  areas, 
  from 
  
electromagnetic 
  pros-­‐ 
  pecting 
  equipment, 
  distributed 
  computing 
  control, 
  highly-­‐parallel 
  web 
  crawling, 
  to 
  iOS 
  apps. 
   
  
Nazanin 
  Samadifard, 
  Machine 
  Learning 
  Specialist, 
  is 
  an 
  accomplished 
  scientist 
  with 
  extensive 
  knowledge 
  and 
  experience 
  in 
  
multidisciplinary 
  research, 
  programming, 
  machine 
  learning, 
  and 
  data 
  analytics. 
  She 
  holds 
  a 
  M.Sc. 
  degree 
  in 
  Physics 
  from 
  the 
  
University 
  of 
  Ottawa 
  and 
  M.A.Sc. 
  in 
  Chemical 
  Engineering 
  from 
  the 
  University 
  of 
  Toronto. 
  
 
  
 
  
Briefly 
  describe 
  any 
  holes 
  in 
  your 
  leadership 
  team. 
  What 
  are 
  your 
  plans 
  to 
  address 
  any 
  recruiting 
  needs 
  in 
  the 
  next 
  18 
  mos.? 
  
We 
  currently 
  are 
  missing 
  team 
  leaders 
  for 
  marketing 
  and 
  sales, 
  business 
  development, 
  operations, 
  senior 
  chemist 
  and 
  human 
  
resources. 
  In 
  the 
  next 
  18months 
  we 
  plan 
  on 
  hiring 
  team 
  leaders 
  for 
  these 
  areas 
  of 
  the 
  business. 
   
  
 
  
KEY 
  ADVISORS 
  and 
  their 
  contributions 
  to 
  date: 
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
  
Dr. 
  Louis 
  Florence 
  is 
  a 
  Finance 
  faculty 
  member 
  & 
  Director 
  of 
  the 
  Undergraduate 
  Programs, 
  School 
  of 
  Management 
  University 
  of 
  
Toronto 
  has 
  extensive 
  business 
  and 
  finance 
  experience. 
  Past 
  President 
  of 
  a 
  software 
  training 
  company, 
  which 
  he 
  founded 
  in 
  1984 
  
and 
  sold 
  in 
  1998. 
   
  
Larry 
  Wilson, 
  32 
  over 
  years 
  of 
  business 
  experience, 
  former 
  National 
  Board 
  Secretary 
  & 
  President 
  of 
  The 
  American 
  Chamber 
  of 
  
Commerce 
  in 
  Canada. 
  Current 
  Trade 
  Commissioner 
  in 
  Canada, 
  for 
  City 
  of 
  Surprise 
  AZ, 
  and 
  in 
  this 
  capacity 
  he 
  initiated 
  Tellspec’s 
  
relationship 
  with 
  the 
  AZ 
  TechCelerator. 
   
  
Simon 
  Mou 
  a 
  strategic 
  investor 
  currently 
  developing 
  a 
  37-­‐acres 
  of 
  land, 
  comprising 
  200 
  new 
  residential 
  homes 
  in 
  S/W 
  Ontario. 
  
Career 
  in 
  finance, 
  held 
  Senior 
  Management 
  positions 
  in 
  corporate 
  finance, 
  lending 
  and 
  retail 
  banking 
  at 
  HSBC 
  subsequent 
  to 
  
engaging 
  in 
  several 
  management 
  positions 
  at 
  TD 
  Canada 
  Trust. 
  Former 
  Director 
  of 
  the 
  United 
  Way 
  Blossom 
  Ball, 
  past 
  Senior 
  Director 
  
of 
  Toronto 
  Chinese 
  Business 
  Association.