Artificial intelligence is the connective tissue of nearly everything we build. We work on the models, agents, and learning systems that let machines perceive, reason, and act — and, just as much, on keeping that intelligence open, legible, and accountable to the people it serves rather than sealed inside a black box.
Canonical machine view: /v1/fields/artificial-intelligence
Wlcro brings consumer-grade fintech to the people and places incumbent banks treat as edge cases. We build payment rails, identity, and credit primitives that work first for the underserved — and turn out to work better for everyone.
TurfDynamics gives enterprises a defensible way to make their hardest calls. It turns scattered data, competing priorities, and tacit expert judgment into structured, auditable decision models — so a team can see exactly how a choice was reached, weigh the trade-offs by role, and revisit it when the facts change. Every decision carries its evidence, its dissent, and its versioned history, which means the organisation can both stand behind the call today and learn from it later.
Auspicia brings the world's oldest spatial sciences — Vastu Shastra and Feng Shui — into a form a machine can reason over. We pair certified practitioners with spatial diagnostics that turn directional and elemental priors into clear, testable guidance for the spaces people live in and build. Every room has a direction; every direction has meaning, and we make that knowledge legible to both the homeowner and the algorithm.
Human body as a machine treats physiology as an engineered system — inputs, control loops, failure modes, and maintenance schedules. We model the body's subsystems with the rigour engineers bring to machines: where the levers are that keep it running well, and what the earliest signals look like when something drifts out of spec. The aim is a shared, falsifiable model of the body that a clinician, an engineer, and an agent can all read from the same page.
Tetralign is a platform for organisational alignment — getting a whole team pointed at the same outcomes without flattening the disagreement that makes a decision good. It pulls strategy, objectives, and the day-to-day signals of how work is actually going into one shared, legible picture, so leaders and contributors can see where they're aligned, where they've drifted, and what to do about it. Alignment stops being a quarterly offsite ritual and becomes something a team can measure and steer continuously.
gistmode turns the firehose of the news into something you can actually hold. It reads across many sources, verifies a story against more than one of them, and distils each into a short, sourced card — never more than a glance — with the image that makes it stick. The result is a feed that respects your attention: the gist first, the depth on tap, and a clear line back to where every claim came from. Built to be read by people and by the agents that increasingly read on their behalf.
What does web infrastructure look like when the primary reader is a model, not a person? Indexing, provenance, and retrieval built for the second user.
Can the priors inside Vastu and Feng Shui be expressed as structured constraints a generative model can reason over — and tested against real outcomes?
Context-aware identity that travels across devices and the human/agent boundary. What does login mean when the "user" is an autonomous process acting for you?
Semantic diffing and bidirectional adapters so systems talk across versions without anyone rewriting the world every time an API moves.
How far can open, self-hosted LLMs go on real financial and planning tasks before cost or accuracy forces a frontier model? Benchmarks welcome.