Inspiration

What it does

How we built itAbout the Project — Sigmyra

Inspiration

The pharmaceutical industry generates an enormous amount of data from digital channels, medical literature, market access updates, and real-world signals. What inspired us was the gap between having data and making confident, timely decisions.

Most existing tools stop at dashboards or alerts. They show what is happening, but not what should be done, why it matters, or how risky a decision is. We wanted to build something that helps teams decide, not just analyze.

That idea became Sigmyra — an always-on Decision Intelligence platform for pharma.

What We Learned

While building Sigmyra, we learned that:

Explainability is as important as accuracy in regulated industries.

Decision-makers need context, prioritization, and traceability, not raw signals.

AI is most powerful when combined with human-in-the-loop workflows.

Governance, auditability, and trust are not “nice to have” — they are essential in pharma.

We also gained deeper insight into how Commercial, Medical, and Market Access teams differ in how they evaluate risk and urgency.

How We Built It

Sigmyra was built as a modular, end-to-end platform:

We ingest and analyze market signals using AI-driven analysis.

Insights are scored and prioritized using configurable decision logic.

Each recommendation is enriched with:

risk assessment,

explainable score breakdown,

recommended actions,

historical context from past decisions.

A Streamlit-based interface enables rapid prototyping and clear storytelling.

The system includes governance features such as decision logs, audit trails, and outcome tracking.

We intentionally designed Sigmyra to be technology-agnostic, scalable, and ready for enterprise integration.

Challenges We Faced

The biggest challenges were:

Designing scoring logic that is transparent and adjustable, not a black box.

Ensuring consistency of data structures across many evolving modules.

Balancing advanced AI features with usability and clarity.

Handling edge cases such as missing data, historical gaps, and evolving schemas.

Building a system that feels both innovative and compliant.

Each challenge pushed us to simplify, modularize, and focus on real-world usability.

What Makes Sigmyra Different

Sigmyra is not just another analytics tool. It is a decision layer that sits above data, helping teams understand:

What matters most right now

Why a recommendation is made

What action should be taken

How confident we can be

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for Sigmyra

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