Frequently asked questions

Integration is typically done in phases. First, we map current control points and communication protocols (BACnet, Modbus, or simple relay interfaces). For many sites we deploy non-intrusive sensors and run AI models in parallel to validate recommendations. Where direct control is required, we implement a supervisory layer that issues setpoint suggestions to the existing BMS or provides operator prompts. A phased approach reduces operational risk and allows staff to validate changes during a short trial.

Outcomes depend on site conditions and objectives. In practical case studies we observe improvements in environmental stability, more timely maintenance actions, and clearer records of indoor air quality trends. Improvements are measured against baseline data collected during the audit and pilot. KintaTair focuses on measurable operational outcomes—reduced variability, faster detection of anomalies, and cleaner data for decision-making—rather than absolute performance promises.

A pilot typically lasts 4–12 weeks. Timeline: week 1 for site audit and installation, weeks 2–6 for data collection and model calibration, and remaining weeks for validation and operator training. The exact duration is scoped based on the facility size and the complexity of integration with existing controls.

KintaTair follows a data minimization and role-based access approach. Sensor telemetry can be anonymized and stored on secure cloud infrastructure located in approved regions, or processed on-premises when required. Access controls, encrypted transport (TLS), and audit logs are part of standard deployments. Specific arrangements can be outlined in the pilot agreement to meet corporate or regulatory requirements.

We provide operational handover documents, remote monitoring options, and service agreements for routine sensor validations and software updates. Support packages are tiered to match the needs of ongoing analytics, on-site inspections, and any firmware lifecycle requirements.

Device selection depends on target analytes. KintaTair assembles sensor suites tailored to scenarios—particulate sensors for manufacturing dust control, VOC sensors for chemical operations, and CO2 for densely occupied spaces. The AI layer correlates multiple signals to reduce false positives and produce context-aware alerts, calibrated using site-specific samples and short validation tests.

Recommendations are translated into step-by-step standard operating procedures during the pilot. We run scenario-based training sessions where staff apply AI-driven alerts to daily routines, and we iterate on alert verbosity, escalation paths, and dashboard views so that guidance aligns with existing workflows.

Start with a scoping audit: provide floor plans, occupancy patterns, and any recent air quality or HVAC logs. KintaTair will propose a pilot footprint, estimated sensor count, and a measurable objective (e.g., stabilize humidity within a defined band during peak production). A short on-site visit can usually finalize feasibility within one week.