Latris

Evidence-native modelling

Build a causal case you can defend — and others can follow.

If your work comes down to a causal argument — the drivers, the evidence, the theory of change behind a decision — Latris is where you build it, justify it, and make it land.

Today that lives in a sketch in Miro, a draft in ChatGPT, citations in a reference manager, and a report in Word — and the reasoning only really exists in your head. Latris pulls it into one place: every link has a reason and a source, AI helps you draft while you stay in control, and what comes out is clear enough that the people who need to act on it can see exactly why.

Latris is in invite-only early access. If we've spoken, you're already set up — download and sign in with your email. Otherwise, get in touch and I'll get you access.

macOS & Windows installers available · Linux coming soon.


Good thinking gets lost in the gaps.

Building the model is only half the job. The other half — assembling the evidence behind every link, recording what you considered and ruled out, turning it into something a client or reviewer can trust — is slower, and it's where the work falls apart. Provenance scatters across five tools, and six months later no one can say why a particular arrow is on the page.

AI makes this sharper, not softer: the easier it gets to generate a model, the more every relationship needs a reason to exist. And the tools built for this are either a decade out of date or so specialised that only their author can drive them — so the findings never really leave your screen.


Where Latris fits

Built for work like this.

Latris suits any work where the reasoning is causal and the stakes make it worth defending — causal maps, driver trees, theories of change, risk and reliability models. A few of the places it fits:

Environment & natural resources

What's driving change in a catchment or ecosystem — and which interventions actually move the needle?

Natural hazards & risk

How the factors behind a hazard combine, where the risk is most sensitive, and what the evidence says.

Public health & wellbeing

Mapping the causes behind an outcome to target where action will help most.

Policy & strategy

Theories of change that make the assumed cause-and-effect explicit, sourced, and reviewable.

Infrastructure & engineering

Reliability and failure reasoning, with the evidence behind each link kept on the record.

Consulting & advisory

Turning a client's messy problem into a defensible, sourced model — and a report they can trust.

Latris speaks a growing set of model types — with one evidence and workflow layer underneath all of them:

Available now Causal loop diagrams Directed acyclic graphs Fuzzy cognitive maps
Coming soon Bayesian networks System dynamics Causal DAGs Markov chains / MDPs Influence diagrams Decision trees Event trees Fault trees Bow-tie diagrams Theory of change Fishbone / Ishikawa Argument maps Goal structuring notation Petri nets Process maps / flowcharts State machines

Don't see your field or your method? The underlying approach is general — if your reasoning is causal, it probably fits. Get in touch and tell me what you're working on.


Why Latris

Defensible

Every link has a reason and a source. Provenance, evidence, and challenge are built into the model — so when someone asks "why is this arrow here?", there's an answer, not a shrug.

Clear

Your model becomes something others can follow — a clean diagram, a sourced report, a plain-language walkthrough — without you in the room to narrate it. Honest about what it can't say, because the uncertainty is measured, not spun.

Fast

AI drafts and reviews while you stay in control. One tool instead of five. Get to a credible, sourced model in an afternoon — fast enough that you actually do the defensible version.


Built for the moment it leaves your desk.

Findings that travel

Most modelling tools assume you'll be standing next to the screen, explaining. Latris assumes you won't. The same versioned model produces what each audience needs, and the reasoning travels with it — click any claim and trace it back to the evidence behind it.

Board-ready diagram

A clean, grid-aligned picture of the system — presentation-quality without a trip through another tool.

Sourced report

The written case, with every claim tied to its evidence and assumptions made explicit.

Plain-language story

A walkthrough for the stakeholder who just needs the "why" — no jargon, no prior knowledge assumed.

One model, three audiences — all from the same source of truth.


For the people who own the decision

When the model isn't yours, but the risk is.

If you commission, sign off, or inherit model-backed work, you carry the risk without having built the thing. Latris gives you the answers you actually need: what assumptions drove this result, who changed what and when, which version backed the decision, and whether another team could pick it up in eighteen months. The full history is kept automatically — Latris becomes the institutional memory around the analysis, not just the place it was drawn.


A note from the founder

I'm Shannon Bengtson — I design and build Latris. I've spent enough time around people who build the causal case behind a decision to watch the same thing happen again and again: careful reasoning gets built in a hurry, the evidence behind it lives in scattered documents, and six months later no one can say why a particular arrow is on the page.

Latris is the tool I wished existed — structure, provenance, and AI assistance that keep pace with the work, so the result holds up when someone asks hard questions, and travels to the people who need to act on it. It's early, and the people I'm bringing on now genuinely shape where it goes. If that resonates, I'd love to hear from you.

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Love to work with you

Latris is early, and the best way to shape it is to use it. Tell me what you're modelling, give it a real go, and let me know what works and what doesn't. I'll get you set up.