Multi-industry AI

Purpose-built AI, industry by industry.

Techotsu builds software for seven industries, each running on its own network of small, specialized AI models — not one general-purpose model stretched thin. Our flagship, Project Reflex, is already screening for early health signals in healthcare; six more industries are on our roadmap.

See our industries Become a pilot partner

techotsu-cli

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✓ Screening complete — result: within typical range

Live demo of the Project Reflex CLI — real command, simulated output

Flagship product — built and tested

Industries on our roadmap

Many, small

Purpose-built models — not one giant model

Software

One architecture, built module by module

Instead of pointing a single general-purpose model at every problem, each Techotsu software module runs a small network of models trained for that exact task.

A software professional working focused at a laptop

Purpose-built models

Each module runs models trained for its specific task — not a repurposed general-purpose chatbot.

Networks, not monoliths

Multiple small models — detection, classification, quality-checking — work together instead of one model doing everything.

Domain-specific training

Models are trained on data and constraints specific to each industry's problems, not generic web text.

Modular by design

Modules and their underlying models are added and upgraded independently, industry by industry.

Built for real constraints

Small models are faster to train, easier to validate, and simpler to deploy where general-purpose models struggle.

Human-in-the-loop, by default

Systems like Project Reflex are built to screen and refer, keeping qualified people in the decision loop.

Real code from Project Reflex — not stock photography

Screenshot of report_stage.py from the Project Reflex backend, showing three separately named models — detection_quality_model, normality_classifier, anisocoria_detector — each logged against its own model run — backend/pipeline/report_stage.py — three separately named models per scan, not one model claiming the result

Screenshot of registry.py, the module registry that maps a module name to its pipeline of stages — backend/registry.py — module registry

Screenshot of detect_stage.py showing the pupil/iris detection stage — backend/pipeline/detect_stage.py — detection stage

Terminal screenshot of certbot issuing a real Let's Encrypt certificate for techotsu.com — Our actual deployment — HTTPS via Let's Encrypt

Industry

Seven industries, one model philosophy

Healthcare is live today. The remaining six are in active development — clearly marked as roadmap, not shipped products.

Live · Flagship

Healthcare — Project Reflex

An AI-assisted screening system, built and tested. Several purpose-built models — detection, classification, quality-checking — work together to screen for early health signals from a photo. Reflex screens and refers to a doctor; it does not diagnose.

A doctor performing an eye examination on a patient in a clinical setting

In development

Retail

Inventory and operations.

In development

Manufacturing

Quality inspection and traceability.

In development

Transportation & Logistics

Visibility and routing.

In development

Hospitality

Guest service and inventory.

In development

Field Operations

Connected field service.

In development

Mobile Technology for Energy & Utilities

Field inspection and asset monitoring.

Techotsu Research

Early-stage · Exploratory

Applying small, physics-aware models to open scientific problems

We're applying the same small-model, physics-aware approach behind our industry software to open problems in science, starting with astrophysics — using real, open astronomical datasets.

Many dynamical equations, such as multi-body orbital motion, have no closed-form solution and must be solved numerically. We're exploring how physics-informed machine learning can accelerate that numerical solving — the same way physics-informed ML is speeding up numerical approximation elsewhere in science.

This means faster, more efficient numerical approximation of known-hard equations — not "solving the unsolvable." This work is exploratory and kept separate from our commercial industry products.

Real, open data sources

NASA Exoplanet Archive
Gaia (ESA)
Sloan Digital Sky Survey (SDSS)

Starting focus

Numerical approximation of multi-body orbital dynamics and related equations with no closed-form solution.

Services

How we work with early partners

Techotsu is early in its industry rollout. Here's how organizations work with us today.

Pilot programs

Trial Techotsu software in your real operations, starting with Project Reflex in healthcare.

Integration & deployment

We help fit purpose-built model modules into your existing systems and workflows.

Research collaboration

Partner with Techotsu Research on open, physics-aware machine learning problems.

Seeking pilot partners

Project Reflex is built and tested in healthcare. We're now looking for a small number of pilot partners to help validate our approach in real-world settings — in healthcare, and across the industries on our roadmap.

Get in touch connect@techotsu.com