UK Ltd · Company No. 16997140 · D-U-N-S 234531872 · Founder building since 2015 · No offshoringUK Ltd · Company No. 16997140

Production software for systems with real failure cost

Production software · real failure cost

Serious engineering for systems that cannot fail quietly.

Trebuchet Dynamics builds production software for scientific compute, infrastructure, validation engines, GPU systems, and agent runtimes. Founder-led delivery. No offshoring.

6Inspectable public repositories and shipped apps
5+Additional production systems delivered under NDA
2015Founder building production systems since

Proof before promise

We build systems where failure has real operational cost, and we design accordingly: legal identity, source ownership, delivery evidence, and a clear engagement model kept ready for procurement review.

Registered
UK Ltd · Company No. 16997140
D-U-N-S
234531872
Audit Trail
Public repos + Google Play
Procurement
NDAs, MSAs, DPAs
Engagement
Discovery → Build → Handoff
Team
Founder-led · No offshoring
Engagement Model

Discovery → Build → Handoff.

  1. DiscoveryFixed-price discovery produces a signed technical spec, risk inventory, and build estimate.
  2. BuildSenior engineers keep priorities visible, CI green, and operational risks on the critical path.
  3. HandoffSource, docs, runbooks, and release discipline are prepared for systems the client must own.
Procurement Ready

Vendor facts are easy to verify.

  • Trebuchet Dynamics Limited, registered in England & Wales
  • D-U-N-S 234531872 for vendor records
  • IP assignment, NDAs, MSAs, DPAs, and full-confidentiality work supported
  • Central Time / North American business-hours aligned in-house engineering team; no offshoring

Open-source audit trail for hard systems.

Public repositories, shipped apps, and source-backed research tools make the engineering audit trail inspectable before procurement. Six shipped public systems are available to inspect. Arenatón is in development, Protein Statera Go is PRD-ready, and additional production systems remain under NDA.

Go-native runtime replacing fragile deployment assumptions
Production-safe Polymarket V2 trading flows with local signing boundaries
Source-backed validation and reporting engines
Delivery story

Runtime recovery under hostile installs

Fragile Python and shell assumptions failed on Termux + locked-down Linux hosts.

Go-native runtime paths made install state observable, recoverable, and easier to support remotely.
Artifact: install diagnostics traceprobe: PATH, shell, storagerecover: durable session streamreport: actionable next step
Delivery story

Trading migration after trust model shift

Older EOA-based Polymarket flows broke when deposit-wallet signing became the production boundary.

polygolem isolated local signing, live market reads, and operator-safe execution paths.
Artifact: signing-boundary diagramwallet: deposit-onlysigning: localexecution: bounded risk
Delivery story

Research validation made inspectable

Scientific tools needed more than outputs: reviewers needed to see source-backed evidence paths.

Moscovium and Cosmos work expose decay-chain traversal, residual reports, and cited validation artifacts.
Artifact: source-backed report previewsource → modelresidual → reportcitation → review

Infrastructure

Runtime and market infrastructure where deployability, signing boundaries, and operator recovery matter.

Gateway runtime operational
AI Agent Runtime

Gormes Agent

Go-native agent runtime with operational gateway work for dependable installs, diagnostics, and recoverable sessions.

  • Single Go binary
  • Offline diagnostics
  • Durable streams
Public trading infrastructure
Prediction Markets / Go Infra

polygolem

Single Go binary and SDK for production-safe Polymarket V2 trading with local deposit-wallet signing boundaries.

  • Deposit-wallet only
  • Local signing
  • Live market data

Scientific Systems

Research tools and source-backed engines built for repeatable validation, reporting, and review.

Public research toolkit
Scientific Computing

FeCIM Lattice Tools

Desktop research stack for FeCIM simulation workflows, references, and validation harnesses.

  • 7 workflows
  • Go/Fyne desktop
  • Validation harnesses
Public research codebase
Nuclear Physics / Research

Moscovium Statera Go

Source-backed nuclear-data engine for isotope records and auditable alpha-decay traversal.

  • DOI-backed data
  • Decay-chain engine
  • Zero-CGO WebGPU
Public research toolkit
Cosmology / Relativity

Cosmos Statera Go

Cosmology and relativity toolkit for residual-first model comparison against observed datasets.

  • Lambda-CDM/NFW
  • Rotation curves
  • Residual reports
Start-ready PRD
Protein Structure / Validation

Protein Statera Go

Go workbench plan for confidence, geometry, RMSD, and evidence-bound protein reports.

  • PDB/AlphaFold
  • pLDDT/clashes/RMSD
  • CLI + HTML reports

Product Surfaces

Shipped and in-progress user surfaces that turn specialized systems into usable products.

Live on Google Play
Android / Generative Math

Fractal Forge

Published GPU fractal explorer with deep zoom, high-resolution export, and no ads or tracking.

  • 350+ fractals
  • GPU rendering
  • On-device privacy
In development
Prediction Markets / DeFi

Arenatón

Web and mobile interface for the public 9lives.so prediction-markets protocol on Superposition.

  • Superposition L3
  • 9lives.so
  • Web + mobile

What changes when failure has cost.

  1. 01

    Prove scientific claims against source data

    Residual reportsCitation pipelinesValidation harnesses
    FeCIM, Moscovium, Cosmos, Protein
  2. 02

    Recover operators from broken runtime assumptions

    Offline diagnosticsDurable sessionsGo runtimes
    Gormes Agent, polygolem
  3. 03

    Turn complex systems into usable product surfaces

    AndroidFlutterVue/AstroField UX
    Fractal Forge, Arenatón
  4. 04

    Render and validate GPU-heavy computation

    VulkanWebGPUGLSLCompute shaders
    Fractal Forge, WebGPU shells
  5. 05

    Make AI/data workflows observable before they fail

    Local LLMsRAGVector searchDiagnostics
    Gormes Agent

Founder-led engineering

Led by Juan Manuel (principal engineer, building production systems since 2015) with 3 in-house engineers. Senior review stays close to the work: architecture, implementation, demos, and source handoff stay connected. The relevant background is physics, mathematics, Go, Rust, and C# applied to lower-risk handoff for systems with real failure cost.

No offshoring

Senior engineering stays close to architecture, code, demos, and handoff.

Visible delivery

Weekly checkpoints, working software, green CI, and explicit priorities.

Client ownership

Source, docs, runbooks, and release process move toward a lower-risk handoff from day one.

Answers before the first call

What's your day rate or typical engagement size?

Engagements run from 4-week sprints (~£40k) to multi-year builds (£250k+). We work in fixed-scope phases, not hourly billing. Rate cards shared after a discovery call.

How long is discovery before we commit money?

1–2 weeks, fixed-price. You leave with a signed technical spec, risk inventory, and a fixed-price scope estimate for the build phase. No commitment to proceed.

Do you sign IP assignment and standard MSAs?

Yes to both. Source, docs, and runbooks are owned by you from day one. NDAs, DPAs, MSAs, and full-confidentiality engagements are routine — we adapt to your procurement.

What if our lead engineer leaves mid-project?

Continuity is the studio's responsibility, not yours. The founder leads every engagement; in-house engineers shadow critical paths. If anyone leaves, we backfill at our cost — no schedule slip charged to you.

Start with the hard part.

Send the problem, constraints, timeline, and decision process. We'll respond with whether the engagement model is the right next step.