Operational Intelligence · Quantum Projects

Operational
intelligence
for quantum projects.

QuantumLog is building local-first software for quantum and frontier research teams. Starting with Yagoda Console, a multi-workflow system for run visibility, calibration context, benchmark movement, alerts, reproducibility snapshots, and project evidence.

Observe what changed. Preserve what matters. Build with confidence.

Local-first
No cloud upload required
Multi-wf
Adapter-based architecture
Full-ctx
Run, drift & snapshot context
Signal Monitor
Demo
DRIFT
Calibration 98.7%
Drift Analysis 94.1%
Observability 91.3%
Gate fidelity ↓ 3.7%
Drift threshold exceeded 12 min ago
02
The Problem

Quantum work
loses context
across tools.

01
Calibration drift becomes invisible
Settings change across runs. Without baseline comparison, history, and alerts, the source is usually found too late.
02
Benchmark movement hides inside workflow complexity
Performance changes across experiments, but teams often lack one view of what changed, when, and why.
03
Reproducibility breaks when context is missing
A successful run is hard to repeat when instrument state, calibration context, parameters, and dataset references are scattered.
04
Research workflows fragment across tools
Teams work across frameworks, scripts, notebooks, logs, datasets, and configuration files without one operational layer between them.
03
Core Layer

One ops layer for quantum workflows.

A local-first infrastructure layer that connects tools, frameworks, scripts, datasets, logs, calibration records, and custom formats into one operational console. Drift, benchmarks, reproducibility, and evidence in one place.

Workflow Inputs
Experiment frameworks
Calibration workflows
Scripts & notebooks
JSON / CSV / HDF5
Instrument logs
Operational
Intelligence
Core
Operational Layer
Run visibility
Drift & benchmarks
Reproducibility
Alerts & snapshots
What changed?
04
Who it is for

Built for teams
working across
quantum tools.

Quantum projects rarely live inside one clean system. Teams work across frameworks, scripts, datasets, notebooks, calibration records, benchmark histories, instrument logs, configuration files, and custom research formats.

01
Research teams

University groups, independent researchers, and collaborative projects that need run visibility across complex workflows.

02
Quantum hardware teams

Teams calibrating and benchmarking systems that need to track drift, movement, and instrument state.

03
Quantum software builders

Teams working with circuits, jobs, datasets, and backend benchmarking who need operational visibility.

04
Lab environments

Local infrastructure, sensitive data, and mixed tooling where cloud upload should not be required by default.

05
Early-stage builders

Projects building operational infrastructure before a full observability stack is justified.

06
Frontier science teams

Experimental teams using custom workflows, non-standard data formats, and project-specific research processes.

05
Products

Product family for quantum operations.

Yagoda Console logo
01 · First product

Yagoda Console

The first QuantumLog product: a local-first console for run visibility, calibration context, benchmark movement, alerts, reproducibility snapshots, and sample data workflows.

Yagoda means strawberry in Bulgarian. Inside QuantumLog, it also works as a product acronym:

Yield Analysis Gradient Observation Drift Awareness
Open Yagoda Console →
Connection layer

Research workflows connected without replacing the tools.

Yagoda sits above frameworks, scripts, notebooks, datasets, logs, and project-specific formats. The goal is not to claim official integrations too early. The goal is to make operational context visible across the workflows teams already use.

QCQCoDeS-style
QFQuantify-style
QBQibolab
QOQibocal
LQLabOne Q
QSQiskit
H5HDF5
PYNotebooks
Sova AI logo
02 · Planned reasoning layer

Sova AI

A planned reasoning layer for QuantumLog. Sova AI is designed to help teams understand alerts, compare selected runs, identify reproducibility risk, and summarize what changed across local project data.

Sova is not designed to control instruments or execute experiments. It supports human review with grounded operational context.

Sova ExplainExplain alerts using local project context.
Sova CompareCompare selected runs against stable references.
Sova RiskFlag weak reproducibility evidence and missing context.
Sova IntegrityDetect suspicious configuration or workflow changes.
Sova MemoryTrack repeated issues, decisions, and ignored alerts.
Privacy-firstFlexible deployment depending on project requirements.
Roza logo
03 · Future product

Roza

To be announced. Roza is part of the future QuantumLog product family, but the project is not publicly described yet.

06
Roadmap

From test group to frontier intelligence.

01
Now
Building a partnership and test group

Selected researchers, builders, labs, and communities validate real workflow problems.

02
Yagoda Console

Local-first run visibility, calibration context, benchmark movement, alerts, and reproducibility snapshots.

03
Sova AI

Future reasoning layer for explaining alerts, comparing runs, identifying risk, and summarizing what changed.

04
Roza

To be announced.

05
QuantumLog Intelligence Layer

Long-term direction: all-in-one operational intelligence for quantum and frontier science projects.

08
Our Thesis

Quantum is ready.
The ops layer is not.

01
The infrastructure gap is real.

Teams operate blind across calibration cycles and workflow transitions. Environment changes go undetected. Run history stays fragmented across tools.

02
The data exists. It is not legible.

Runs, calibration logs, benchmark histories, and metadata are scattered across frameworks. No single view shows what changed and when.

03
Operational context becomes the moat.

As quantum projects mature, the teams that can preserve, compare, and reason over operational context will move faster with greater confidence.

08
Partnership

Partnership and test group.

QuantumLog is looking for selected research teams, builders, labs, universities, and communities that want to validate the first operational layer for quantum and frontier science workflows.

01
Join the test group

Share the workflows, tools, datasets, and project context your team works with.

02
Validate the problem

Review whether Yagoda Console matches real operational gaps in your research or development process.

03
Run a controlled pilot

Future pilots can run locally or in a controlled environment. Data should stay inside the team infrastructure by default.

04
Shape adapter priorities

Relevant workflows can influence which adapters and formats QuantumLog prioritizes first.

09
Partners

Partners and supporters.

QuantumLog is building with support from selected universities, communities, research groups, and ecosystem partners.

Partner logos will appear here as collaborations are confirmed.

University partner
Community partner
Research partner
Ecosystem partner