High case volumes and thin margins demand efficient integration—not another proprietary platform to maintain.
Build custom AI service agents using Python SDKs and headless APIs. Connect your appliance telemetry, CRM, and warranty systems without vendor lock-in through standard REST endpoints and open integration patterns.
Agents need context from warranty systems, IoT telemetry, parts catalogs, and CRM records. Building custom integrations to each system creates maintenance burden and brittle connections.
Legacy contact center platforms trap you in closed ecosystems with limited extensibility. Custom workflows require expensive professional services and cannot be version-controlled in your own repository.
Pre-trained models fail on appliance-specific failure modes and symptom patterns. You cannot retrain on your historical case data or adjust classification logic when the model misroutes refrigeration cases to HVAC specialists.
Bruviti provides headless APIs and Python SDKs so you build service intelligence into your existing stack. Connect appliance telemetry streams, warranty entitlement databases, and parts catalogs through standard REST endpoints. Train custom models on your historical case data using your own Python notebooks—no vendor professional services required.
The platform exposes case classification, knowledge retrieval, and response generation as discrete API calls. Route results to your CRM, trigger workflows in your ticketing system, or surface recommendations in your agent copilot. All integration code lives in your repository under your version control. Switch orchestration layers or swap out components without rebuilding the entire contact center stack.
Automatically classify refrigerator error codes from customer emails and route to warranty validation APIs before agent assignment.
Train custom symptom classifiers on 5 years of dishwasher case history to predict part failures before dispatch.
Call summarization API ingests transcripts and generates structured JSON with detected model numbers and failure symptoms.
Appliance manufacturers handle 50,000+ daily contacts during peak HVAC and refrigeration seasons. Connect IoT telemetry streams from connected appliances directly to case context APIs. When a customer calls about a refrigerator issue, the agent sees last 30 days of temperature fluctuations and compressor cycle counts pulled from the appliance's cloud connection.
Integrate warranty entitlement databases through batch sync APIs that refresh daily. The knowledge retrieval endpoint queries parts catalogs, service bulletins, and historical case resolutions simultaneously—returning ranked answers with source citations in under 200ms. Route all responses through your existing CRM's case management system to maintain single source of truth.
Python 3.8+ and TypeScript are fully supported with official SDKs. The REST API accepts standard JSON payloads so you can integrate from any language. Python SDK includes notebook examples for training custom classifiers on your case history. All API endpoints use OAuth2 authentication and return structured responses with OpenAPI documentation.
Yes. The platform provides model training APIs that ingest your historical case data, failure symptom patterns, and resolution outcomes. Train appliance-specific classifiers for refrigerators, dishwashers, and HVAC units using your own Python notebooks. Export trained models for local inference or host them on Bruviti infrastructure—you retain full ownership and export rights.
Connect warranty databases through batch sync APIs that run on your schedule—daily overnight updates are typical. Parts catalog integration uses real-time REST endpoints so agents always see current inventory and pricing. The platform includes pre-built adapters for SAP, Oracle EBS, and common ERP systems. All integrations run in your VPC with credentials you control.
All trained models can be exported in standard ONNX format for inference elsewhere. Your integration code lives in your repository—switching providers means pointing API calls to a new endpoint. Case data, telemetry, and knowledge bases remain in your systems since Bruviti operates as a stateless layer over your existing infrastructure. No data migration required.
Four to six weeks from kickoff to production for a single use case like email triage or case classification. Week 1 covers API authentication and data pipeline setup. Weeks 2-3 focus on model training using your historical data. Weeks 4-6 handle integration testing and phased rollout to agent groups. Most teams deploy additional use cases in 2-3 weeks after the first integration is live.
Transforming appliance support with AI-powered resolution.
Understanding and optimizing the issue resolution curve.
Vision AI solutions for EV charging support.
Talk to our solutions architects about integrating Bruviti into your appliance service stack.
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