TrueLoop is a model-free, retained-state feedback runtime — adaptive control and optimization middleware. It sits between the application or model that sets your objective and the wave or parametric substrate that realizes it: you give it a measured statistic and a target or score each round, and it returns the next configuration to apply. Because it converges from a single measurement per round, it lets you run a control or optimization loop you already have at a harder operating point — fewer measurements, faster cadence, higher dimension, more drift, a tighter deadline — than a classical loop permits.
Every round has three steps: you measure your system at the current configuration, you send that measurement (and a score) to the runtime, and you receive the next configuration to apply. The update law runs on the NEOTECH endpoint — you never receive it, so there is nothing to leak in either direction.
copyfrom swc import SWCOptimizer
opt = SWCOptimizer(license_key="EVAL-...", n=len(x0))
x = opt.start(x0)
for _ in range(rounds):
p_hat = measure(x) # one measurement -> a vector
x = opt.step(p_hat, score=objective(x))
opt.end()In the hosted model, yes: because the update step runs on our endpoint, the client reaches it once per round. Only lightweight numbers cross the wire — your configuration vector and a scalar score — not your raw data, and nothing is retained past the session. Each round adds one HTTPS round-trip (tens to low-hundreds of milliseconds), which is negligible when the measurement itself is the expensive part: a batch of quantum shots, an ultrasonic scan, a lab experiment.
Where the hosted model is the wrong fit: microsecond, high-rate real-time control, where you cannot afford a network hop per step. For those cases — and for air-gapped or data-residency requirements — any paid license unlocks running the runtime offline in your own systems: the same loop, no per-round network hop, your infrastructure. You can prototype on the endpoint during the free evaluation, then move the exact same integration in-house for production. See pricing.
The advantage is concentrated, not universal: tight measurement budgets, drift, and latency-bound loops. The runtime ships with an envelope check that tells you — honestly — when you are in a winning regime and when your current method already does the job. See The envelope.