Existing systems
We build on the infrastructure and tools you already run, rather than asking you to replace them.
AI Systems Development Partner
Complex AI systems,from concept to production.
Building a model is rarely the hard part. The hard part is making it actually work inside existing systems, real data, the way people already do their jobs, and the conditions it has to run under. a3gent designs all of that together and ships it as one product.
Approach
We design systems that run — not just models
AI projects usually stall somewhere outside the model. We treat these four as part of the work from day one.
Data
Medical imaging, physiological signals, voice — data that arrives in every format and quality, handled as real input.
User workflows
Not just showing a result, but designing the path from that result to the next decision a person has to make.
Operating conditions
Security, validation scope, failure behavior, who maintains it — settled before the system goes live, not after.
0public demos you can try
0body systems in SOMA's full-body twin
0skin sites with 3D tissue sections
0stages from import to surgical simulation
01 · Built solutions
Start with what already works
Each solution below has a public demo you can try. When you adopt one, we agree on its scope for your environment.
Biosensing · Digital Twin
Public demo · Research use
SOMA
A biosensing digital twin for wearable-sensor experiments. Place virtual sensors on a full-body anatomy, vary physiological conditions, and explore the synthetic signals that result.
- Full-body twin — 6 body systems, 3D tissue sections at 12 skin sites
- ECG · PPG · EEG · EMG · respiration synthesis, with CSV export
- Sleep apnea — respiration from a sternal patch, across postures and movement
- Wrist sensing — capacitive arrays over the radial artery, pulse transit (PTT/PWV) research
Dental · 3D Planning
Public demo · Research use
OralPilot
An implant planning studio that connects 3D anatomy, periodontal charting, implant placement and surgical simulation in a single flow.
- DICOM · STL · X-ray input — files are processed only in the browser
- 3D exploration of teeth, jaw and mandibular canal, plus periodontal chart
- Rule- and geometry-based engine that drafts position, angle and size
- Guide geometry review and step-by-step surgical simulation
02 · Case studies
What, how — and how far
Rather than a list of experience: for each case, the problem, the part that actually works, and the part that has not been validated yet.
Experiment with the signal before building the sensor
SOMA · Biosensing digital twin
Problem
A wearable's signal changes sharply with placement, posture, movement and tissue. Checking that normally means building hardware and repeating human-subject trials, so early design decisions are slow and expensive.
Solution
Anatomy, sensor placement, physiological conditions and signal synthesis combined into one experimental environment. Researchers see how the signal responds first, then narrow down the real experiments.
What works today
- Sensor placement and synthetic signals, whole-body and local
- Scenario screens for sleep apnea and wrist sensing
- CSV export of signal data
Validation scope
A research environment built on synthetic signals. Continuous blood-pressure estimation and independent validation are designed as the next stage. Not for clinical decisions.
Scattered clinical data, one planning flow
OralPilot · Implant planning studio
Problem
CBCT, intraoral scans, X-rays and periodontal records live in different tools and formats. Implant planning needs all of them at once — in practice, clinicians switch tools and combine them in their heads.
Solution
Six stages — import, 3D exploration, periodontal exam, implant planning, guide review, surgical simulation — joined into one on-screen flow. Clinical files never leave the browser.
What works today
- DICOM · STL · X-ray import and 3D structure exploration
- Placement drafts that respect clearance to key structures and neighboring teeth
- Virtual extraction aligned to the tooth axis, and staged simulation
Validation scope
Rule-based geometric search, not a trained model, validated on public cases for research use. Automatic segmentation and CT–scan registration are not yet implemented; it does not estimate bone quality or judge clinical safety.
Capabilities
The experience behind these cases
Voice AI
Speech recognition and synthesis that hold up under real-world noise, latency and conversational flow.
Automation
Repetitive judgment and processing, connected across existing tools into automation you can actually operate.
Medical data & products
Products that handle medical imaging and physiological signals — from data processing to interface to defining what is validated.
Engineering leadership
Experience leading development teams, so technical choices are weighed against schedule, staffing and maintenance.
03 · How to engage
Two ways to work with us
Take only what you need. Adopting a solution is often enough on its own; custom development is added when it has to reach deep into your systems.
Solution adoption
What you purchaseA license to an existing service or technology, plus the cost of deploying it
- Fast deployment of a proven solution
- Installation and configuration for your environment
- A clear agreement on scope and validation
Best when your problem closely matches what an existing solution was built to solve.
Custom development
What you purchaseHands-on engagement to integrate, extend and validate against your systems
- Integration with your existing systems and data
- Features extended to fit your workflows
- Validation designed around your own data
Best when a solution needs to be fitted closely to systems and workflows unique to you.
Talk to us
Start with the problem you want to solve
- 1Inquiry
Tell us the problem and the systems you run today.
- 2Scoping
We separate what existing solutions cover from what needs building.
- 3Proposal
Solution adoption, custom development, or a combination.
- 4Agreement
We agree on scope and validation criteria, then begin.
Contact
Contact details coming soon.