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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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SOLUTIONS

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AI Intelligence Engine for Commercial Real Estate

Transform commercial real estate decision-making with AI-powered intelligence. Unify fragmented data, automate insights extraction, and optimize asset management—eliminating inefficiencies, reducing risks, and unlocking new revenue opportunities.

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AI Engine for Autonomous Monitoring and Detection

Enhance manufacturing efficiency and asset reliability with AI-powered autonomous monitoring. Detect anomalies, prevent costly downtime, and ensure safety compliance—eliminating inefficiencies from reactive maintenance and manual oversight.

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AI Engine for Patient Intake and Triage

Transform patient intake and triage with AI-driven automation. Accelerate care delivery, reduce administrative overhead, and ensure precise patient prioritization—improving efficiency, reducing wait times, and enhancing patient outcomes.

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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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AI
Coming Soon

How AI is Solving Healthcare's Operational Challenges

The healthcare industry stands at a pivotal moment of transformation. While technological advances have revolutionized medical treatments, many healthcare organizations still grapple with operational inefficiencies that cost billions annually. In view of this, recent developments in AI, particularly Google Cloud's introduction of MedLM, are rapidly changing this landscape. As highlighted in Google Cloud's recent announcement, these AI solutions are moving beyond theoretical applications into real-world implementation across various healthcare operations.

AI
Coming Soon

AI in Clinical Labs: A Guide to Transforming Operations

Clinical laboratory teams have barely caught their breath. After the marathon of COVID-19 testing volumes, they've transitioned straight into managing surging routine diagnostics while simultaneously implementing new technologies and striving for greater efficiency. As we move through 2024, artificial intelligence (AI) is emerging as the key to transforming how clinical laboratories operate, promising to revolutionize everything from sample processing to result delivery.

Generative AI
Coming Soon

The LLM Mirage: Why Dazzling Prototypes Often Crumble in Production

Many organizations find that promising LLM prototypes struggle in real-world applications. This blog post examines the challenges that arise when moving from AI prototypes to production systems. We discuss key issues including scaling difficulties, data privacy concerns, and system reliability problems. Learn how to bridge the gap between prototypes and production, and discover approaches to ensure successful deployment of AI technologies in your organization. Gain practical insights for overcoming common pitfalls and developing robust, valuable AI systems that meet real-world business needs.

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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