Intelligence-driven evidence

Intelligence-driven evidence

Buyers want proof.
Payers want outcomes.
Clinicians and patients want confidence.
Boards want ROI.

Our technology combines deep healthcare intelligence with rigorous evidence generation to deliver all of it.

Buyers want proof.
Payers want outcomes.
Clinicians and patients want confidence.
Boards want ROI.

Our technology combines deep healthcare intelligence with rigorous evidence generation to deliver all of it.

  • Our engine gets smarter,

    and smarter

  • Our engine gets smarter,

    and smarter

  • Our engine gets smarter,

    and smarter

Every engagement strengthens our intelligence layer. Each study we conduct, each regulatory pathway we navigate, each outcome we measure adds to the platform's knowledge base. This means our evidence strategies improve over time—informed by an expanding dataset of what works across the healthcare innovation landscape. The more cases we handle, the more precise our risk identification, the more effective our study designs, and the faster we generate compelling evidence.

How it works

Augura integrates three tightly coupled capabilities that reinforce each other:

Strategy Optimization

Before designing a study, we analyze what's worked historically — and what makes your specific innovation different. Our risk intelligence engine combines years of regulatory data, adverse event patterns, and real-world outcomes with a forward-looking assessment of your solution's unique risk profile. We stratify risk based on clinical stakes: an AI making diagnostic decisions carries fundamentally different evidentiary requirements than one automating administrative workflows. We surface hidden opportunities, anticipate regulatory questions specific to your use case, and design studies calibrated to the actual risk your innovation presents — not a one-size-fits-all template.

Strategy Optimization

Before designing a study, we analyze what's worked historically — and what makes your specific innovation different. Our risk intelligence engine combines years of regulatory data, adverse event patterns, and real-world outcomes with a forward-looking assessment of your solution's unique risk profile. We stratify risk based on clinical stakes: an AI making diagnostic decisions carries fundamentally different evidentiary requirements than one automating administrative workflows. We surface hidden opportunities, anticipate regulatory questions specific to your use case, and design studies calibrated to the actual risk your innovation presents — not a one-size-fits-all template.

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Evidence Generation

We design and execute studies that generate the evidence the ecosystem requires. For connected technologies — devices that stream data, software that logs usage, apps that track outcomes — we integrate directly to capture real-world performance. For those without native data streams, we leverage our intelligence platform to draw on comparable cases, historical benchmarks, and proxy indicators that inform risk and opportunity. Our methodology combines pragmatic trial design, causal inference, real-world evidence and health economics to produce evidence that meets both regulatory standards and commercial requirements.

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Evidence Generation

We design and execute studies that generate the evidence the ecosystem requires. For connected technologies — devices that stream data, software that logs usage, apps that track outcomes — we integrate directly to capture real-world performance. For those without native data streams, we leverage our intelligence platform to draw on comparable cases, historical benchmarks, and proxy indicators that inform risk and opportunity. Our methodology combines pragmatic trial design, causal inference, real-world evidence and health economics to produce evidence that meets both regulatory standards and commercial requirements.

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Evidence Documentation

We convert analytical outputs into the formats stakeholders require: regulator-ready submissions, payer dossiers, clinical evidence summaries for sales teams, governance reports for boards. Traceable, auditable, and continuously updated as new evidence accumulates.

Smiling man with light brown hair and stubble, wearing a khaki shirt in natural light

Wonder how things work in details?

Let's schedule a moment to dive into specifics.

Contact us

Contact us

Smiling man with light brown hair and stubble, wearing a khaki shirt in natural light

Wonder how things work in details?

Let's schedule a moment to dive into specifics.

Contact us

Contact us

Our approach

  1. Start with the end in mind

Who needs to be convinced — and what decisions will this evidence support? We start with the buyer, payer, or clinician you need to persuade — then design the study to answer their questions.

  1. Learn from what's worked

Before designing a protocol, our platform analyzes comparable cases, outcomes, and clinical settings. What convinced similar buyers? Which designs generated the most compelling data? Your study benefits from intelligence gathered across the healthcare innovation landscape.

  1. Balance rigor with reality

Perfect evidence that takes three years doesn't help you sell today. We design efficient pragmatic studies that achieve statistical rigor within realistic timelines and budgets — adaptive designs, efficient endpoints, smart use of existing data.

  1. Gather data where it lives

For connected technologies, we integrate directly with data streams. For deployed systems, we capture real-world performance in your environment. For technologies without native data, we leverage comparable cases and proxy indicators. We use decentralized approaches — remote monitoring, EHR integration, patient registries — to generate evidence without traditional site-based trial overhead.

  1. Deliver evidence that gets used

We produce documentation in the formats that matter: clinical evidence summaries for sales teams, health economics models for payer conversations, manuscripts for publication, governance reports for boards, regulatory submissions.