Healthcare
01
A clinical intelligence layer, built with proprietary open-weight models, that reads a patient's full history and answers with citations a clinician can check.
AI architecture, model-agnostic by design
The architecture is the intelligence.
We build reliable AI systems.
architecture, mathematically
The architecture is the function.
We define architecture as a function of the task, its context, the available models, and the constraints. Design that function well and the system pulls the right memory for each task and routes it to the model that fits best.
architecture
=
f
(
task
,
context
,
models
,
constraints
)
routing sends each task to the model that fits it best
the persistence layer
A model forgets. An architecture should not.
Memory is the foundational layer. We build the architecture on top of it: a knowledge graph for structure, vector embeddings for recall, and a router that learns from outcomes. The system hands a task its full context in one prompt instead of rebuilding it every session.
Why memory matters. The intelligence of a task is not only the model. It rises when the system builds the right context and retrieves it at the right moment. Get memory right and every answer improves, even after the model is frozen.
how we work
Built on frameworks we can prove.
We are research-driven and work from first principles. Every engagement runs the same loop.
01
First principles
strip it to what is true
02
Deep research
read everything that matters
03
Plan
design before we build
04
Execute
ship to production
05
Learn
measure, then improve
work
Systems in mission-critical industries.
Where output accuracy is paramount.
Mergers and M&A
02
A complete deal-flow pipeline that saves hours and widens the research, surfacing prospective buyers and sellers a team would otherwise miss.
Consulting
03
A proprietary deep-research framework that compresses weeks of analysis into enterprise-ready briefs.
High-ticket sales
04
A go-to-market engine that uses deep research, lead enrichment, and channel automation to book more first meetings.
the hypothesis
One architecture. Many models.
An architecture should not depend on the intelligence of a single model. The architecture of the future delivers reliable output no matter which model it runs on. That is our hypothesis.
evals, audit, proof
Measured, audited,
and reproducible.
and reproducible.
Outputs are scored against ground truth, every decision is logged, and the verdict reproduces on a cold run.
one architecture
many models independent of the model
many models independent of the model
95-98% frontier
LLM quality on routed tasks
LLM quality on routed tasks
50% cost
efficiency same quality, half the spend
efficiency same quality, half the spend
frameworks
you can prove measured, reproducible
you can prove measured, reproducible
a question to leave you with
If a system only works because the model is smart, what happens when the model changes?
A great architecture does not depend on the model being smart. It works no matter which model runs underneath.