Engine Nominal
0000
Quantitative · Modeling · Scientific · Software

Hard problems, working tools

Tythys turns quantitative reasoning, modeling, and scientific thinking into software you can actually use — focused tools, validated against real results, priced for the people who need them.

Σ
Quantitative Reasoning
Modeling
Scientific Thinking
Problem-Solving
The Four Pillars

What Tythys is built on — and tested against

Every product on this site exercises at least one of these. Every decision — what to build, what to ship, what to refuse — gets measured against them.

Σ
P01

Quantitative Reasoning

Numbers that mean something

Turning vague questions into measurable ones. Units, scales, error bars, sanity checks — the discipline of reasoning with numbers instead of about them.

P02

Modeling

Math that mirrors reality

Finding the equations and abstractions that capture how a system actually behaves — beam under load, portfolio under risk, signal under noise.

P03

Scientific Thinking

Hypothesis · test · revise

Treating each tool as an experiment: state the assumption, validate against known results, fail loudly when wrong, ship only what holds up.

P04

Problem-Solving + Software

From insight to interface

Compressing the loop from "I think this is the model" to "anyone can run it" — clean code, validated outputs, a UI that respects the user.

Operating loopreason    model    test    shiprepeat
Platform

Focused tools for real problems

Each tool below is one of the four pillars made tangible — quantitative reasoning, modeling, scientific thinking, or problem-solving compressed into something you can run, validate, and rely on.

🛰️
Live

Vertical SaaS

GatewaySight

API Gateway observability for reliable operations

Monitor gateway health, trace request flow, and detect latency or error spikes early so your team can resolve incidents faster.

Compute Metrics
PillarsΣ
⚙️
Live

Engineering Simulation

EngineerCalc

Beam deflection & structural calculators

Beam deflection, bending stress, support reactions, and safety factors for the four most common load cases. Validated against Roark's Formulas.

CalculusPhysics
Pillars
⚛️

Engineering Simulation

PhysicsSim Pro

Structural & fluid simulation for engineers

Affordable web-based physics simulations for small firms — structural loads, fluid dynamics, thermal analysis. No $50K license required.

CalculusPhysicsNumerical Methods
Pillars
📈

Quantitative Finance

PortfolioSigma

Monte Carlo portfolio & risk modeling

Options pricing, portfolio optimization, and Monte Carlo retirement simulations — scoped to what can be implemented correctly right now.

Stochastic ProcessesStatisticsLinear Algebra
PillarsΣ
🧮

EdTech

MathCanvas

Interactive math & physics visualizations

Animated, manipulable explorations of calculus, linear algebra, and physics for universities, tutors, and self-learners.

Linear AlgebraCalculusPhysics
PillarsΣ
🔍

ML / Analytics

AnomalyLens

Anomaly detection for manufacturing & IoT

ML anomaly detection for small manufacturers — no data science team required. Plug in sensor data, get actionable alerts.

StatisticsSignal Processing
PillarsΣ
🧠

Consulting

Custom Models

Bespoke computation & simulation work

Have a specific calculation or modelling problem? Open to scoped projects where the problem is well-defined and the expected output is clear.

Pillars
How It Gets Built

The approach

Each tool follows the same discipline — understand the problem first, implement it correctly, then ship something clean.

01

Frame the Question

Translate a vague need into a measurable one. What are the inputs, the outputs, the units, the failure modes? Quantitative reasoning before code.

02

Build the Model

Find or derive the equations. Implement the core in Python — NumPy, SciPy, or plain arithmetic — and check it against textbook cases and known answers.

03

Test Like a Scientist

Hypothesise, perturb, compare. Edge cases, sanity checks, validation suites. If it disagrees with reality, the model is wrong — not reality.

04

Ship a Tool, Not a Notebook

Wrap the validated core in a clean interface so someone who needs an answer — not a programming environment — can actually use it.

About Tythys

Founder-led.
Methodically built.

Tythys builds specialized analytical tools grounded in quantitative modeling, scientific reasoning, and applied engineering. Each product is designed for correctness, clarity of interpretation, and practical use—not features built for a slide deck.

Work proceeds in small, verifiable steps: compare against established benchmarks, then ship when it earns its place in real workflows. Long term, the goal is dependable software between heavyweight enterprise platforms and fragile, spreadsheet-bound processes.

Python · NumPy · SciPyData VisualizationMonte Carlo SimulationNumerical MethodsLinear AlgebraPortfolio ModelingEngineering CalculatorsPhysics SimulationInteractive EducationAnomaly Detection

∂u/∂t + (u·∇)u = −∇p + ν∇²u

Navier–Stokes

Ax = λx

Eigendecomposition

dS = μS dt + σS dWₜ

Black–Scholes SDE

∇·E = ρ/ε₀

Gauss's Law

δ = PL³ / 48EI

Beam Deflection

Contact

Interested or
just curious?

If one of these tools could help you, or if you have a problem worth building for — send a message. No sales pitch, no commitment.

Response time
Within 48 hours
Stage
Early — building in public
Domain
tythys.com