.webp)
%20(1).svg)
We integrate directly with PLCs (Siemens, Allen-Bradley), SCADA systems, and sensors using OPC UA, Modbus, and edge gateways. Your machines stay in place. The software adapts to them.
Before writing code, we document the current cost, time, error rate, and output of the target workflow. The AI system is measured against that baseline before it scales.
A flag without a reason is a dead end. Every system we build gives operators human-readable explanations for each alert, so the team knows what to check and why.
FDA 21 CFR Part 11, AS9100, IATF 16949, SOC 2 Type II. We build audit trails, e-signatures, and access controls into the architecture from the start, so your platform passes enterprise procurement without a last-minute scramble.
You own the code, the AI models, and the design. No per-seat licenses, no recurring SaaS fees, no platform dependency. The system runs on your infrastructure and scales without asking permission.
We ship systems that handle high-frequency sensor data across multiple facilities, run 24/7, and survive growth from one line to fifty plants. The architecture is built for the volume before the volume arrives.
The 923 team was fantastic to work with and taught me a lot about ML and AI.
These are the builds industrial teams ask for most, each one scoped to their equipment and data.
Yes. We connect directly to PLCs from Siemens and Allen-Bradley, SCADA systems, and industrial sensors using OPC UA, Modbus, and MQTT. For equipment that lacks digital outputs, we install edge gateways and retrofit sensors to digitize analog signals. The Wheels Now project shows this in practice: we integrated a legacy ERP system with a custom web app to give the sales team real-time inventory access.
No. Most industrial sites we work with start in that state. We build the data pipeline first: ETL processes, daily snapshots, and labeled training data from historical records. For Amerit Fleet, we built a pipeline from 300,000+ mechanic comments in a single SQL database with no version history, and turned it into a reliable training dataset.
We design compliance into the architecture from day one: audit trails, e-signatures, role-based access controls, encryption at rest and in transit, and validation documentation. We are SOC 2 Type II compliant. Your platform passes the procurement review instead of stalling it.
A focused proof of concept runs 6 to 8 weeks. A production system, from discovery through deployment, typically runs 90 days. We start with a discovery phase to map the workflow, establish the baseline, and give you a fixed scope and budget before writing code.
You own everything: the code, the AI models, the design, and the data pipelines. No per-seat licenses, no recurring platform fees, no vendor lock-in. The system runs on your infrastructure. Most industrial AI projects range from $150K to $500K depending on the number of equipment integrations and the complexity of the models.
Bring us your hardest operational problem and we will scope a custom AI build around it. From connecting legacy PLCs to deploying predictive maintenance models, we handle the engineering so your team can keep the line running. Clients like Amerit Fleet cut error detection time by 90% and saw 10x ROI.
Meet with founders Andrew Amann & Pavel Kirillov
Custom AI implementation roadmap
No sales pressure
