Notable Projects

A selection of noteworthy projects are listed below. Please reach out with any questions or inquiries.

LLM-enabled data analysis & storytelling

ChartArt a natural language question and answer service, allowing users to query and analyze data without needing technical or data analysis expertise. Currently in private beta.

  • Product mission: To reduce the barriers, cognitive load, and time-to-insight in data processing, analysis, storytelling.
LLM
  • 🎯 Key activities and Outcomes:
    • Product Launch: We teamed up with the founding and engineering teams to design, and launch ChartArt.ai, an on-demand assistant designed to streamline data analysis and storytelling.
    • Product Development: Working closely with the team to enhance the assistant dialogue model, focusing on its ability to accurately understand and respond to data-related queries, generate insightful prompts, and boost its skills in quantitative and visual analysis
    • Go-To-Market(GTM): Crafted the GTM strategy and created messaging, product explanations that match the user’s state of mind and varying needs. Successfully reduced churn by 20%, improved product engagement, and boosted trial-to-paid conversions and retention rate
  • Established a single framework to align everyone, on how to communicate the product value as well as unifying the team around goals, and key metrics

Care delivery

Platform for chronic population and patient communities

Care Delivery

  • Objective: Roll out care delivery model that support a range of hybrid care options
  • 🎯 Outcomes: We partnered with founding team to define and deliver the core capabilities (through collaborative efforts with Engineering, Service Design, and Clinical Ops) including:
    • A member-focused mobile experience
    • CareOps building blocks: care delivery workflows, service blueprints, and a web experience enabling multiple modalities of care (in-person primary care, at-home care, virtual) across different settings (rural, urban, suburban) in key markets
    • Successful integration with health gorilla FHIR APIs to streamline clinical data exchange workflows, improving patient data retrieval process by 8x

ML-as-a-service

for a global telecom provider

MLP

  • Objective: Reduce internal Machine Learning development, validation and deployment efforts and decrease time-to-value by 10x
  • 🎯 Outcome: Together with a multi-disciplinary team, we have laid the groundwork for a robust machine learning program and launched ML-as-a-service characterized by the following features:
    • A user interface for managing models (select and deploy models as an API endpoint)
    • Guided workflows for training and deploying models
    • A pipeline for ingesting data from a variety of sources
    • A data discovery tool to preview raw data and discover quantitative attributes like mean, median, and mode

Navigating Treatment, Trials, and Testing

The platform intended for oncology patients as well as health providers

O4Me

  • Objective: Provide evidence-based knowledge to aid and empower patients in navigating their medical choices including clinical trials, and relevant testing possibilities
  • 🎯 Outcome: Together with a lean team, achieved the following:
    • Launched an information retrieval system integrated with a mobile experience, enabling the identification and comparison of relevant clinical trials, tailored to individual patient profiles.
    • Enhanced the experience with a treatment information feed feature and digital tools for symptom monitoring and note-taking
    • Significantly enhanced patient access to critical information, substantially reduced the effort in navigating diagnosis and treatment options

ML-Roaming operations for global telecom

for a global telecom provider - wholesale division

MLP

  • Objective: Utilize Machine Learning (ML) to unlock the value of the large amount of data captured within the data lake - primarily to support two usecases:
    • Steering Optimization
    • Inbound Market Share
  • 🎯 Outcome:
    • We collaborated with BU leaders, ML engineers, data scientists, and Google to create and launch predictive models for steering errors and network violations
    • Enhanced steering optimization accuracy and cut traffic to forbidden networks
    • Delivered key insights on roaming KPIs, like steering ratios and targets.