Burns & complex wounds
Tier-1 and 2 hospitals with active burns and wound units. Predictive grafts where tissue composition, bed readiness, and print params decide outcomes.
R&D co-pilot from image to printable graft design
Bioprint the exact graft your body needs. From a wound image to tissue mix, bioink, and print params - computed, not guessed.
Backed by researchers and early capital.
Partnered with research and clinical labs.
Tvashtr BiotechTvashtr BiotechTvashtr BiotechWe turn a wound photo into a graft you can print.
Generic grafts fail to integrate; autografts wound the donor site. Zyogen turns a photo into printable bioink, scaffold, and params. On-prem, DPDP & HIPAA ready.
Read the wound as tissue. A photo becomes a ViT class map before anything is printed.
ViT locked geometry and class patches. Majority granulation with fibrin islands and a thin epithelial rim.
Score bioink blend and printability. Area fractions and physics lock the recipe inside the wet-lab envelope.
Area fractions set the bioink blend; physics scored the recipe inside the wet-lab envelope.
granulation58.0%
fibrin19.0%
epithelial14.0%
necrosis9.0%
Area fractions drive bioink blend and scaffold porosity.
recipe confidence0.910
scaffold porosity0.68
normalized area4.72 cm2
Recipe confidence and wound area after vision normalization.
Forecast the graft take path. Diffusion conditioned on day-0 tissue mix and heal rate.
Median recovery ~24 days. Scrub the timeline.
Diffusion conditioned on tissue mix and heal rate. Median recovery ~24 days - scrub the timeline.
Healing forecast · day 0 · rate 0.71
day 0day 0day 30
Forecast progress · day 0
Overall healing15%
Epithelial coverage8%
Graft integration12%
Collagen maturity5%
Granulation activity58%
Wound burden25%
Curves are conditioned on day-0 tissue fractions and heal rate - they move with the timeline scrub, not measured follow-up imaging.
See the wound as tissue, not pixels.
A vision model maps the bed patch by patch: granulation, fibrin, epithelium, necrosis. Graft design starts from what is actually there.
Biology, software, and trust in one stack.
Interpretability as trust
We audit model internals so predictions key on real tissue biology, across the tissues we print, not rulers, lighting artifacts, or demographic shortcuts.
Hospital-first for India, then global. SaaS and per-graft pricing 30 to 40% below imports.
Ophthalmology
Corneal and ocular surface programs adopting clinical imaging workflows. Clear SaMD-style routes for prediction software beside the surgeon.
Orthopedics
Cartilage and soft-tissue reconstruction teams already running bioprinters from Cellink, Regemat, 3D Systems, and NBIL in research hospitals.
Research labs
Tissue engineering labs at IITs and AIIMS. India R&D runs 70 to 80% cheaper: build the stack here, then export the method.
SEA & MENA hospitals
Secondary expansion markets where India’s cost advantage compounds. Same hospital SaaS + per-graft model, priced below imported stacks.
US & EU bioprinting centres
Global expansion after proving deployment in India. FDA SaMD and EU MDR routes for clinical prediction software already exist.
Team
product and tissue engineering.
Founder & CEO
Built and exited ImpactPlay for cancer patients. Robotics and medtech projects with acquired IP. AI Growth & Insights @ Google (via Canvas8). IEO International Rank 6. 3× valedictorian.
Prof. Falguni Pati
Scientific Collaborator
HOD Biomedical Engineering, IIT Hyderabad. 7,700+ citations, 100+ publications. First author, Nature Communications (2014) on decellularized-ECM bioinks.
Questions & Answers
Learn more about predictive bioprinting with Zyogen.
No. Zyogen automates structure, consistency, and parameter suggestion. Your clinical team leads interpretation and the final graft decision.
No. The stack is deterministic. A physics engine computes bioink formulation, scaffold geometry, and print parameters from wet-lab data, not hallucinated outputs.
A vision model maps wound-bed composition, granulation, fibrin, necrosis, and related conditions. Those fractions feed predictors for whether the bed can take a skin graft and how healing is likely to run.
Medical models can secretly key on rulers, skin tone, or lighting. We audit internals so the system is trusted for the right biological reasons before it informs a decision.
Sovereign deployment: self-hosted and on-prem inside hospital infrastructure, designed for DPDP and HIPAA compliance.
Yes. A hardware translation layer produces toolpaths and extrusion protocols for multi-modal bioprinters already installed in research and clinical settings.
Work with us
Hospitals, research labs, and partners building the predictive layer for regenerative care.