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Accelerate your journey, from Data to AI

Data Driven
phase
01

Data Strategy

Craft a visionary plan for unparalleled data-driven success

Data Aware
phase
02

Data Foundations

Build a rock-solid data infrastructure for limitless scale

Data Assisted
phase
03

Data Integration

Connect, converge, and unlock the power of unified data

Data Driven
phase
04

AI Innovation

Innovate at the speed of AI by transforming data insights into actions

Data Intelligent
phase
05

AI in Production

Deploy intelligent AI models for your products to boost productivity and delight customers

01
Data Strategy
02
Data Foundations
03
Data Integration
04
AI Innovation
05
AI in Production
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Join the leading enterprises and industry disruptors who work with Bitstrapped

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SOLUTIONS

Explore our tailored solutions

Healthcare Document Intelligence

Healthcare documentation processes are still heavily paper-based, which is tedious, error-prone, and time-consuming. Manual data entry and reliance on physical documents slow down healthcare delivery and can lead to inaccuracies that affect patient care.

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GenAI POC Accelerator

Developing AI solutions from scratch can be a time-consuming and resource-intensive process. Organizations often struggle with the complexity and high costs associated with creating robust AI prototypes and proof of concepts.

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Restaurant AI

Today's diners expect a seamless online experience. Manual handling of customer inquiries and reservations can put a load on staff and affect customer satisfaction. Restaurant AI provides a solution through a user-friendly chatbot that streamlines pre-sale interactions, personalizes the dining experience, and empowers you to capture more online orders.

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Celebrating customer success

Predictive Maintenance for Oil and Gas Supermajors

Cloud-based simulations to predict failure of equipment and improve the efficiency of maintenance operations

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Event-Driven Kubernetes pipelines for high performant at-home patient health monitoring systems

Reducing patient falls — a billion dollar cost to the healthcare system, can be combatted with help of Kubernetes Engine

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Predictive responsiveness in neurological recovery therapy

Medical devices and robotics company leverages machine learning to launch predictive models to classify the level of responsiveness of in-home neurological recovery therapy

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Generative AI
Coming Soon

Automating Medical Documentation Process with Generative AI

While the demand for digitalization and automation is rapidly growing, many healthcare organizations continue to battle with outdated paper-based methods and legacy digital platforms, leading to inefficiencies and challenges in patient care delivery. By automating tedious tasks and enhancing information accessibility, generative AI has the potential to transform the way healthcare professionals interact with patient data, ultimately improving efficiency, accuracy, and overall quality of care.

Generative AI
Coming Soon

Leveraging Open Source for Automatic Background Removal in Photo Editing: A Step-by-Step Look at the Technical Approach

Discover the power of open-source AI with tools like Mask R-CNN and Samsung's Lama for automatic background removal and seamless inpainting in photography. Learn how these technologies, combined with Google Cloud Platform, offer scalable solutions for high-quality photo editing accessible to all.

Generative AI
Coming Soon

Introducing QARL: A Generative AI Tool to Remove the Risk from your LLM Applications

Introducing QARL, a cutting-edge AI testing framework developed by Bitstrapped and Alaska Airlines to enhance the safety and efficiency of conversational AI. QARL uses generative AI to automate testing at scale, ensuring LLMs adhere to brand and ethical standards before public release. Discover how QARL streamlines the development process, improves performance, and boosts customer experiences in AI applications.

Do it right the first time,
with our proven path to success.

85% of machine learning models end as experiments. Don't take chances, work with Bitstrapped to avoid the pitfalls and blindspots at the (3) stages of the machine learning journey:

1

ML Readiness

  • Validate data and objectives
  • Organize, Clean, Augment, Enrich datasets
  • Prototype initial models for validation
2

Infrastructure for ML

  • Establish foundational Infrastructure for ML
  • Put your Data platform and tooling to work
  • Architectures to train, evaluate, validate, monitor, and deploy models
3

Scale and Operate ML

  • Special Ops teams to manage
    and evolve ML environments
  • Ongoing Cloud platform management
  • Roadmap planning and strategic wins

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