Production AI,
built with your team.
We co-develop machine learning systems for problems off-the-shelf AI can't handle, from a scoped proof of concept to a model your engineers run themselves. Every prediction comes with calibrated uncertainty, so your team knows when to act and when to escalate.
Looking for our marketing science platform? Alviss AI lives at alviss.io
Trusted by teams at
When the problem is yours alone, we build it with you
Our researchers work alongside your engineers. The code lands in your repo, the knowledge transfers with it, and your team can run the system after we step back. For healthcare, finance, manufacturing, infrastructure, and defense teams that can't afford overconfident predictions.
Deployed into your stack, on-prem or air-gapped for sovereign and regulated environments.
What we've built
- ▸Healthcare & life sciences: diabetic retinopathy from retinal scans, skin cancer triage from photos, drug-discovery virtual screening with AIChemy, together with RG Discovery.
- ▸Finance: probabilistic stock-interval prediction for AI Alpha Lab, budget optimisation for a top-3 insurer that cut sales spend by up to 25%.
- ▸Manufacturing: drone-based surface inspection of wind turbine foundations with Quali-Drone and Bladt Industries (now part of CSW Offshore).
- ▸Infrastructure: autonomous road-defect segmentation with Robotiz3d, 25x faster than the point-cloud approach it replaced.
- ▸Defense & dual-use: the same drone inspection, terrain and damage segmentation, and perception that abstains when unsure, for situational awareness and force protection. Human-in-the-loop, deployable on-prem or air-gapped.
Small first step, honest answer
Most clients start with a scoped proof of concept and grow from there. You decide after each stage whether to continue.
- 1Week 0
Scoping call
A 30-minute call with one of our researchers. Bring the problem and a rough idea of your data. We tell you honestly whether a model can help, and what a first step would look like.
- 24 to 8 weeks
Proof of concept
We agree on a success metric up front, build on your data, and report whether it meets the bar. If the data is not there, you know early and cheaply.
- 32 to 4 months
Production pilot
Code in your repo, inference pipeline, monitoring, retraining. Your engineers pair with ours so they can run it after we step back, on your cloud, on-prem, or air-gapped.
Where we stand on generative AI
Large language models are remarkable at language. They are not calibrated decision-makers: when an LLM is confidently wrong, nothing in the stack tells you. That gap is exactly what we've been building against since 2018.
We're not anti-LLM, we're pro-calibration. When a workflow needs both, we co-develop systems where language models handle the interface and Borch models make the calls that carry risk, with uncertainty attached to every one.
Built on Borch
Borch is our open-source deep universal probabilistic programming language, built on PyTorch. It makes hierarchical Bayesian models and uncertainty-aware deep neural networks practical at production scale.
Every model we ship, whether a co-development engagement, Alviss AI, or AIChemy, runs on Borch. Your team gets open-source code it can read and extend, not a black box tied to a vendor.
Explore Borchimport torch
import borch
# Any PyTorch module becomes Bayesian in one line.
net = borch.nn.Linear(10, 1)
# Forward pass samples from the posterior.
pred = net(x)
# Loss combines likelihood and KL to the prior.
loss = (pred - y).pow(2).mean() + net.kl_divergence()
loss.backward()
Two productised verticals
Where the same problem kept coming back, we turned our co-development work into products.
Alviss AI
Commercial predictive analytics
Real-time probabilistic forecasting for marketing-mix modelling, demand planning, and commercial decisioning. Uncertainty surfaced as credible intervals, not a single-point prediction.
Visit alviss.ioAIChemy
Drug discovery
Equivariant deep probabilistic graph neural networks for virtual screening. Uncertainty on every compound, so hit lists come with the confidence attached.
Visit aichemy.ioReady for the next step?
Tell us the decision you need to make with confidence. We'll tell you honestly whether a model can help.