Welcome to Mantis,
the data platform for life sciences performance

Mantis is the world's first domain-aware data platform that encodes biological and clinical meaning directly into reusable datasets, enabling teams to answer new questions with queries rather than projects.

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Meet the Team

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Analyze

Collect

Maintain

Analyze

Collect

Maintain

Life sciences organizations generate enormous amounts of biological, clinical, and operational data across specialized systems: EDC, CTMS, lab vendors, omics platforms, manufacturing systems, and more. Each system speaks its own language, uses its own identifiers, and encodes its own assumptions.

We solve this problem

Product Features

Mantis is changing the game in the data analytics world and traditional tools don't even come close.

Reusable datasets, not one-off pipelines

Most life sciences teams answer the same questions over and over by rebuilding the same pipelines.

We replace this with canonical, versioned datasets that persist across teams and time. Once a dataset exists, it can be reused for analytics, operations, AI, and compliance.

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Built to work with the systems you already run

We integrate directly with the platforms you already depend on — EDC, CTMS, lab vendors, CSV, and analytics tools — to serve single, coherent foundation.

We sit above your existing stack, unifying data and encoding meaning so it’s reusable everywhere downstream.

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Reduce terabytes of data into a few key insights

By encoding biological, clinical, and human-performance meaning directly into datasets, we distill complexity into stable, trusted signals that can be reused across teams.

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Multi domain tools don't cut it any more

Life sciences data is too complex for one-size-fits-all platforms.

Generic Data Warehouses

Large-scale data storage

Elastic compute

Domain-agnostic tables

Manual joins across EDC, CTMS, labs

Limited lineage and auditability

Batch-oriented refresh cycles

Fragmented data lakes

Cost spikes at scale

Ontology Platforms

Cross-system integration

Custom domain modeling

Heavy ontology configuration

Consultant-driven deployments

Black-box transformations

Static or delayed operational views

High operational overhead

Slow iteration at scale

Mantis

Domain-aware data models

Canonical biomedical & clinical datasets

Meaning encoded directly into data

Reusable across analytics, AI, and operations

Full lineage to raw source systems

Real-time performance views

On demand custom integrations

Unblock hidden bottlenecks in your development process

Amplify early signals into revenue-boosting actions with our powerful analytics suite.

Early Intervention

Partner Benchmarking

Cross-Study Analysis

AI Readiness

Shorten trial timelines by acting on early execution signals

Bring clinical, operational, and vendor data into a single execution view so teams can see where trials are slowing down while there’s still time to intervene. Instead of discovering delays after milestones slip, teams act on leading indicators of execution in near real time.

Compare site and CRO performance across studies

Create a consistent, longitudinal view of how sites and partners perform across trials and programs. Teams can make reuse and resourcing decisions based on historical execution data, not anecdotes or one-off reports.

Run cross-study analytics without rebuilding pipelines

Enable analysts to ask new questions across trials using the same underlying datasets. Cross-study analysis becomes routine instead of a special project, because definitions and structure are already aligned.

Turn operational data into AI-ready inputs

AI adjusts prices in real-time based on inventory turnover, competitor MAP violations, and customer sensitivity tiers. Clients achieve 14% margin lifts while maintaining brand price integrity.

Early Intervention

Partner Benchmarking

Cross-Study Analysis

AI Readiness

Shorten trial timelines by acting on early execution signals

Compare site and CRO performance across studies

Run cross-study analytics without rebuilding pipelines

Turn operational data into AI-ready inputs

Provide data science teams with consistent, longitudinal datasets that already encode clinical and operational meaning. Models and advanced analytics start from trusted inputs instead of raw system exports.

Shorten trial timelines by acting on early execution signals

Compare site and CRO performance across studies

Run cross-study analytics without rebuilding pipelines

Turn operational data into AI-ready inputs

AI adjusts prices in real-time based on inventory turnover, competitor MAP violations, and customer sensitivity tiers. Clients achieve 14% margin lifts while maintaining brand price integrity.

Why our customers love us

It's not just about features. It's about making our customer's lives easier with the most intuitive analytics tool.

01. We meet them where they are

We build custom integrations into the systems they already run, including legacy and vendor platforms.

01. We meet them where they are

We build custom integrations into the systems they already run, including legacy and vendor platforms.

02. We deliver answers, not just infrastructure

When teams need dashboards, reports, or ad hoc analyses, we build them quickly on top of the same canonical datasets.

02. We deliver answers, not just infrastructure

When teams need dashboards, reports, or ad hoc analyses, we build them quickly on top of the same canonical datasets.

03. Trust and compliance are built in

Our platform is designed for sensitive data from day one. We support HIPAA-compliant workflows and operate with the security and governance standards required by regulated environments.

03. Trust and compliance are built in

Our platform is designed for sensitive data from day one. We support HIPAA-compliant workflows and operate with the security and governance standards required by regulated environments.

04. We nurture adoption

When needed, our forward-deployed engineers work directly with customer teams to model data, ship datasets, and unblock real-world use cases.

04. We nurture adoption

When needed, our forward-deployed engineers work directly with customer teams to model data, ship datasets, and unblock real-world use cases.

05. The platform fades into the background

Once data is stable and reusable, teams stop thinking about infrastructure and focus on decisions, execution, and outcomes.

05. The platform fades into the background

Once data is stable and reusable, teams stop thinking about infrastructure and focus on decisions, execution, and outcomes.

06. Analytics scales without scaling headcount

As demand for insight grows, teams support more use cases without multiplying pipelines or engineering effort.

06. Analytics scales without scaling headcount

As demand for insight grows, teams support more use cases without multiplying pipelines or engineering effort.