Praktice Pitch Deck

Transcript

1. Autonomous Patient Engagement through Medical Artificial Intelligence
2. In short Next 7patients served by our customers per year 75 mn 25 K ($) Number of edges in our knowledge graph mn Estimated Monthly conversations by Dec’18 K By names By numbers Partners / investors / customers Current customers Engaged with 50Estimated least case MRR by Dec’18 Partners & Investors Highlights of praktice.ai Problem we’re solving With the best hospitals of Asia as our existing clientele and who’s who of healthcare industry in our pipeline, we are expecting an exponential growth in our revenue & valuation
3. like Mercy Hospitals(USA), SingHealth Hospitals(SG), Apollo hospitals (IN) Operational staff salaries are contributing to 70% of the manpower cost and it’s set at 20% YOY growth every year, next only to growth in revenue Problem(1) we solve, for tertiary hospitals Problem (2) Reasons ➔ Excessive operational cost With the general inflation, the receptionists, call agents, care coordinator etc salaries are reaching a peak and hospitals need 20% more such staff every year to cater to their growing needs. ➔ Ineffective patient interactions These staff are not medically trained The patient interactions lack medical context & medical knowledge of the patient SingHealth - $1.1 Bn Parkway Pantai - $0.95 Bn 20% increase yoy in this non clinical staff cost
4. Problem(2) Product lug Revenue leakage Selected above are the problem areas which praktice.ai is addressing for hospitals ➔ Missed Patients 15 - 20% of the patients drop off or never reach a consultation stage due to queries in non-office hours, excessive wait times, incomplete / irrelevant responses from patient facing staff ➔ Lost Leads Leads to Appointments ratio is typically less than 20% and patients drop out without booking appointments because of concerns / unanswered queries related to • Cost/insurance • Outcomes • Fears of treatment • Ignorance of the seriousness ➔ No show Globally this is between 15% - 30%. More than half of these slots never get filled & cause revenue loss ~ $600 - $800 mn is the overall revenue lost per year by some of the hospital groups like Parkway Pantai, Bangkok Hospitals etc., Reasons
5. Next Solution Details Our product is our core differentiation, and this is extremely difficult to build as it needs a doctor with data science understanding or a data scientist with medical knowledge. Fortunately we have both! Text Conversational Virtual Assistant on hospital website with Medical Knowledge Triaging ability Multilingual NLU Voice Conversational Virtual Assistant on hospital landline with Contextual Speech Recognition Understanding of Open ended questions * Each of these capabilities, is built in-house, based on deep learning & they’re always improving with robust feedback loops Our product
6. In short Next How is our product solving these problems ? Solution Details Our virtual assistant for hospitals, not just handles the transactional needs of patients, but also proactively engages throughout the journey from problem identification to complete cure • Appointment Booking • Medical symptoms collection • General enquiries / queries • Process related queries • Wait time instructions • Navigation help • Referral letter evaluation • Doctor related information • Proactive Follow-up • Reduction of no-shows • Post consultation follow-up • Prognosis of health condition • Giving information to patient about the previous outcomes of such treatments • Helping patients with insurance / billing related queries • Monitoring symptoms • Proactive follow up for next appointment • Medication & doctor instruction adherence General Physician Specialist / Super-specialist Treatment / surgery Rehabilitation • Triaging & specialist suggestion • Appointment Booking • Appointment management • Insurance related queries • Match-making with the right doctor & optimization of resources
7. In short Next Operational roles that are semi/fully automated with Praktice Enterprise Grade Operational tasks that can be automated only by a medically intelligent technology like that of Praktice.ai which understands patient, just like a nurse or a doctor does
8. In short Next Our pride - Enterprise scale product quality The Team With robust data security & infinite scalability, we can even handle bursts of usage from multiple enterprises. Having proven secure integrations with SingHealth & Apollo, we cut-down our future integration cycles by half Our custom web-bot framework has over 40 different templates which augments NLP input of user We built interface richer and more intuitive than even facebook, intercom & Microsoft We survived a random DDoS attack of 70 GB, and were up and running in minutes with 0 data loss Robust technology architecture with over 15 primary, 30 supporting components & 150 micro-services A strong firewall in the socket server HIPAA compliant systems Stress tested & infinitely scalable In-house developed NER, auto-corrector, speech tuning & image parsing
9. Experienced in managing one of the biggest hospital in India Extensive clinical experience working as a Oral and Maxillofacial surgeon. Responsible for our contextual engine framework. Architected & managed the entire big data & insights system at flipkart Supply Chain. Experience in speech technology of United Airlines & United Insurance, and is a Full stack developer and data scientist Sumit Malpani Chief Product Officer Roadmap Core Team Srinath Akula CEO and Co-Founder Dr. Akhila Adabala COO and Co-Founder Experienced in managing product cycles in technology companies like PolicyBazaar & Snapdeal, and at Praktice, is Responsible for product & project management along with customer account management Doctor with understanding of data & machine learning Data Scientist & Techie with medical understanding The Go-getter Team of 10: ML developers, doctors and data scientists
10. Road Map, Customers & Pipeline Foray into the world’s largest Healthcare market With the healthcare connections & network in place through TechStars & SAP, with vast experience from other markets, we are ready to enter the best market 2019 Entry into Middle East With strong lead to NMC Healthcare, Dubai’s largest private hospital group, we would expand our base into Middle East 2018 Q4 Expansion into rest of Southeast Asia Strong engagement with Parkway Hospitals, Bangkok Hospitals & rest of Singapore public healthcare leading to the next growth phase 2018 Q3 Apollo Hospitals (final stages of negotiation) Contract worth $1.5 million. Combination of a fixed fee and success fee driven, which is on the total revenue generated. Negative Churn Rate 2018 Q2 SingHealth (Successful pilot, procurement phase) Contract worth $1mn. Further use-cases or post treatment and outcome driven. 2018 Q1 Initial pilots & Product development phase With an experience of 250K conversations from our B2C customer conversations, we embarked on discovering PMF for hospitals 2017 Singapore India Southeast Asia United States Middle East & more individual clinics
11. Cost Saving: E.g., Apollo Hospitals • Average appointment cost - $1.7 • Praktice per appt charge - $0.34 • praktice mean payout (ARR) - $360K Business Model & ROI calculations Financial Projections Additional Revenue from qualifying more leads Cost savings Recovered Lost Revenue 1/5th of current Appointment cost 1/10th of recovered lost revenue 1/10th to 1/15th of additional revenue generated Recovering lost revenue: E.g., Parkway Pantai • Average missed appointments per day - 1275 • Missed Revenues - $250mn • Praktice payout - 10% (revenue share) of recovered appointments (~ 10%) - $2.5 mn Additional Qualified leads E.g., Bangkok • If the conversion rate on the digital properties increases by 12%, BDMS gets $89 mn • Praktice payout - 6% (revenue share) of additional revenue = $ 6 mn
12. In short Next Monthly Revenue Projections Competitive Landscape We see an exponential growth starting mid this year, due to the strong product-market fit and a clearly perceived value from hospitals Early pilots revenue - $5000 ~ $15,000 ~ $20,000 ~ $20,000 ~ $5,000 ~ $50,000
13. In short Competitive Landscape While all the closest competitors are in USA, there is no competition in Asia & Australia.Market size for praktice is $40 Billion and, only in Southeast Asia, Middle east & Australia, it is $15 Billion by 2020 Medical NLU Clinical Pathways Patient Engagement Pre-consultation queries Post-consultation queries
14. In short Pilot results With these results, we are not just undergoing the procurement process, and also started working on various other use-cases related to post-consultation, pre- & post-treatment etc., Core objective: Cost saving As our per conversation cost is $1, which is 25% of their current cost, we successfully proved, with over 70% of the conversations autonomously handled, that we can save millions of dollars for the group Second objective: 24x7 availability Over 40% of the conversations were out of office hours, which clearly proved the desirous patient experience Focus on transactions During the pilot, the interacted patients had a variety of queries, and all of these were successfully handled. But the unique distinction was our bot’s laser focus on completing transactions like booking & managing appointments, which it excelled Data Security & Privacy Successfully integrating with a digital health nation which has one of the most stringent data privacy laws is a proof that our systems are water tight Integration with NEHR We integrated with National Electronic Health Records, which covers all public health systems of Singapore, with most of private practices joining the NEHR 05 01 02 03 04
15. Our fundraise plans Technology developers ML developers - 3 Doctors - 2 Web developers - 1 DevOps - 1 Business Development Singapore - 1 Rest of SEA - 2 US (part-time) - 1 Marketing • Conferences • (co-hosting conference in Singapore with SAP) • Participating in other conferences • Content Marketing Technology Infra • Cloud Telephony • Servers to handle TBs of data crunching Fund deployment • Approximate Runway - 1 year • core use of funds: leading the south-east Asian market by capturing all top tertiary care hospital groups in the region Key asks from investors • Warm introductions to top hospital group COOs (or) CEOs • Help in connecting to insurance companies $600K • Projected MRR by April’19 - $120K • Key development areas ◦ Speech integration ◦ Human like understanding of patient’s concerns ◦ Deep learning for advanced revenue & cost optimization
16. akhila@praktice.ai | srinath@praktice.ai