500
Transformers under continuous predictive monitoring across global utility fleets.
Transformer failures cost millions in repairs, lost revenue, and SLA penalties, and replacements are not quick — roughly a year of lead time for medium-voltage units and two to four years at substation level. Harsh loading has pulled service life that used to run 25 years down to under 10. Manual inspection rounds miss the early degradation that would have given operators warning.
Sequoia builds the sensing, edge processing, and cloud platforms that close that gap. Triaxial vibration and temperature monitoring on transformers and rotating machinery. Thermal and optical camera fusion on switchgear. The utility-side control systems that dispatch distributed device fleets, and the multi-tenant IoT platforms behind EV charging, fleet, and fuel operations. We have about 500 transformers and 1.5 GW under management globally, and we stay on through deployment, scaling, and maintenance.
Triaxial vibration and temperature sensors feed edge ML models with cloud predictive analytics behind them, flagging degradation weeks to months before failure. Around 500 transformers and 1.5 GW are under management globally, with continuous coverage across switchgear, transformers, and rotating machinery. Sequoia builds, deploys, scales, and maintains the platform, and it runs for multiple customers today.
Thermal faults in switchgear are expensive and hard to catch on an inspection schedule — hot spots form between checks, and an undetected fault turns into an outage, a safety incident, or damaged equipment. We fuse real-time thermal and optical camera feeds with object tracking and live temperature readout, configurable safe, warning, and danger alerting, and motion and foreign object detection. Continuous automated visibility replaces the manual round.
An electrical OEM needed one platform to serve consumers and utility partners at the same time. We built a layered cloud architecture where the utility control engine and the consumer app each connect to the device fleet through separate interfaces, not to each other — so demand response, frequency control, load shaping, and voltage support run with zero dependency on whether a consumer has the app open or updated. Demand response, time-of-use pricing, and virtual power plant dispatch are configurable per utility partner.
Manual site visits drove up operating cost and slowed response to charger failures across a fast-growing, multi-site footprint. We built a multi-tenant IoT platform — edge gateways, MQTT pipelines, cloud backend, live dashboards — deployed on AWS through Terraform and Ansible, with OCPP, InCharge, and eDRV charger integrations plus auth and observability. More than 100 sites are managed today, with solar, generator, and EV data in one dashboard.
Triaxial vibration and temperature sensors feed edge ML models with cloud predictive analytics behind them, flagging degradation weeks to months before failure. Around 500 transformers and 1.5 GW are under management globally, with continuous coverage across switchgear, transformers, and rotating machinery. Sequoia builds, deploys, scales, and maintains the platform, and it runs for multiple customers today.
Thermal faults in switchgear are expensive and hard to catch on an inspection schedule — hot spots form between checks, and an undetected fault turns into an outage, a safety incident, or damaged equipment. We fuse real-time thermal and optical camera feeds with object tracking and live temperature readout, configurable safe, warning, and danger alerting, and motion and foreign object detection. Continuous automated visibility replaces the manual round.
An electrical OEM needed one platform to serve consumers and utility partners at the same time. We built a layered cloud architecture where the utility control engine and the consumer app each connect to the device fleet through separate interfaces, not to each other — so demand response, frequency control, load shaping, and voltage support run with zero dependency on whether a consumer has the app open or updated. Demand response, time-of-use pricing, and virtual power plant dispatch are configurable per utility partner.
Manual site visits drove up operating cost and slowed response to charger failures across a fast-growing, multi-site footprint. We built a multi-tenant IoT platform — edge gateways, MQTT pipelines, cloud backend, live dashboards — deployed on AWS through Terraform and Ansible, with OCPP, InCharge, and eDRV charger integrations plus auth and observability. More than 100 sites are managed today, with solar, generator, and EV data in one dashboard.
Knowledgewise
Institutional Knowledge for Field Teams
Knowledgewise is Sequoia's in-house accelerator that turns scattered manuals, veteran expertise, and field-specific knowledge into a cited, safety-aware AI assistant — giving every technician on day one the same grounded answers as senior staff.
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Field knowledge lives in scattered manuals, notes, and the heads of experienced technicians — lost when people leave, hard to access for people who just joined
New technicians can't answer like veterans without years of accumulated experience
Different fields need different vocabulary and source-trust rules — a one-size-fits-all assistant doesn't work
Built
Split architecture: one core system (reads documents, searches, writes cited answers) plus a field-specific module (vocabulary, document types, source trust order, behavior rules)
New field added in about 2 days — same product underneath, only the module changes
Asks for clarification on vague questions, says so honestly when something isn't documented, and gets more cautious on safety-related questions with sources always shown
Data kept separate per field and per customer, enforced at the lowest level of the system
Knowledgewise is a production-ready, in-house built accelerator that transforms field knowledge silos into a structured, field-specific AI assistant — with citation transparency, safety escalation, and data isolation enforced at the system level.
Key Capabilities
Transforms scattered manuals, notes, and veteran expertise into a structured, searchable knowledge base that survives staff turnover.
A single core system with pluggable field modules — vocabulary, document types, source trust order, and behavior rules — customized per domain in ~2 days.
Escalates caution on safety-related queries, always cites sources, and honestly acknowledges gaps — engineered for regulated field operations.
Use Cases
Fleet Maintenance
Regulatory docs prioritized first, technician notes last — ensuring every answer respects the trust hierarchy of critical maintenance documentation.
Field Service & Repair
New technicians get grounded, cited answers identical to what senior staff provide — closing the experience gap from day one.
Regulatory Compliance Queries
Instantly surfaces the right compliance guidance across complex multi-document regulatory environments without manual searching.
Onboarding Acceleration
Compresses months of knowledge transfer into immediate access — new hires answer like veterans using the same trusted sources.
Outcomes
Deployed in two proven, very different field environments — demonstrating that the same core product adapts across industries with minimal reconfiguration.
Deployed in two proven, very different fields — fleet maintenance and laptop repair — proving the same core product adapts
New technicians get the same grounded, cited answers as senior staff
Each field respects its own source trust order (e.g., fleet maintenance: regulatory docs first, technician notes last)
How It Works
In-House Accelerator
Knowledgewise
Built and maintained by Sequoia Applied Technologies — field-tested in production environments and ready for enterprise deployment with minimal customization.
Sensing and inference at the asset, analytics and dispatch in the cloud, and platform engineering that holds up across multiple customers and sites.
Triaxial vibration and temperature sensing with edge ML and cloud predictive analytics, detecting failure signatures weeks to months ahead across transformers, switchgear, and rotating machinery.
Systems in production today across grid assets, industrial monitoring, utility dispatch, and EV and fleet operations.
Triaxial vibration and temperature sensing with edge ML and cloud analytics, flagging degradation weeks to months before failure. 500 transformers and 1.5 GW under management globally, with extended asset life and fewer unplanned outages.
Read case studyThermal and optical camera fusion with object tracking, live temperature readout, and configurable safe, warning, and danger alerting — continuous automated visibility replacing manual inspection.
Read case studyOne platform serving a self-install consumer product and utility-grade grid operations at the same time, with dispatch events running independent of consumer app state and new utility partners onboarded through configuration.
Read case studyA multi-tenant IoT platform across 100+ sites with OCPP, InCharge, and eDRV integrations — fewer truck rolls, faster response to failures, and growth in site count without added headcount.
Read case studyFigures from energy and utility systems Sequoia has built and continues to operate — asset monitoring at grid scale, and multi-tenant IoT across distributed sites.
500
Transformers under continuous predictive monitoring across global utility fleets.
Capacity under management
1.5 GW
Continuous monitoring across switchgear, transformers, and rotating machinery, with AI driven flags for potential failures.
EV, Fleet & Fuel Sites Managed
100+
Real-time EV control and fuel alerts, with solar, generator, and EV data unified in one dashboard.
Failure Warning Lead Time
Weeks
Connected technologies, scalable infrastructure, and intelligent operational systems are shaping the next generation of digital transformation across industries.
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