Conceivable Life Sciences

"The World's First Automation-Assisted IVF Lab" — Physical AI applied to embryology to make IVF accessible, consistent, and scalable.

Where it wins

• Precision Robotics & Proprietary Software: AURA's six integrated workstations automate the 200+ precise steps of IVF, replacing manual workflows that struggle with consistency [1].
• Data Flywheel: Every cycle generates granular, standardized process data, compounding models and ensuring continuous product improvement [1].
• Cost Reduction: By cutting the average number of cycles per baby in half through improved outcomes, AURA halves the cost per baby, addressing the primary driver of IVF expenses [1].

Credibility: Claims of over 30 live births and 60+ pregnancies are being proven in an IRB-approved clinical study [1].

• Physical AI Platform: Selling or deploying AURA, a system of six integrated workstations that automate the full IVF lab workflow [1].
• Scale via Automation: Enabling skilled embryology teams to deliver many times more cycles manually by handling the 200+ precise steps with machine precision [1].
• Margin via Efficiency: Capturing value by reducing the number of cycles per baby, thereby lowering the primary cost driver for clinics and patients [1].

• Traditional IVF Labs: Rely on manual workflows, lacking the consistency and scale offered by AURA [1].
• Other IVF Technology Providers: Competing on incremental improvements rather than full automation and data-driven optimization [1].
• Differentiators: Conceivable's AURA is the world's first automation-assisted IVF lab, combining physical AI with a data flywheel to drive scale and cost reduction [1].

• High Cost of IVF: A single IVF cycle costs more than a year's income for many, making it inaccessible [1].
• Limited Access: True demand for IVF is at least 12M babies/year, but only 750,000 are currently born via IVF [1].
• Manual Inconsistency: Traditional IVF labs struggle to maintain consistency across the 200+ precise steps per cycle [1].
• Low Success Rates: Multiple cycles are often required to achieve a live birth, increasing cost and emotional burden [1].

Conceivable's wedge is clear: automation solves the scalability and cost crisis in IVF by replacing manual inconsistency with machine precision. The main risk at scale is regulatory and clinical adoption; proving safety and efficacy in real-world settings is critical. The opportunity lies in the data flywheel, where cumulative cycle data drives continuous improvement, creating a moat. The next signal to watch is the IRB study results; positive outcomes will validate the model and accelerate clinic adoption.

Pursue strategic partnerships with major IVF clinic chains to accelerate deployment and gather diverse clinical data. Develop a clear pricing model that aligns with cost savings for clinics, such as a per-cycle fee or subscription. Expand the data flywheel by integrating with existing lab information systems for seamless data flow. Address patient concerns by highlighting the emotional and financial benefits of reduced cycle counts in marketing materials.