Use cases

Three deployment patterns. One engine.

Truvyo deploys against the same architecture across every vertical. What changes is the audience, the SKU catalog, and which agent (Customer or Technical Companion) carries the workload.

Reference deployment specs

Drawn from real production deployments. Scale linearly with catalog size.

DimensionHardware resellerField service networkDev platform
Primary agentCustomer AgentTechnical CompanionCustomer Agent
Catalog size16–200 SKUs5–50 product lines1 product, deep API surface
Tenant articles200–800500–2,000300–600
Shared Library leverageHigh (vendor PDFs)High (manufacturer SOPs)Medium
First-response time1.4 s1.8 s1.2 s
Tier 0/1 deflection~80%~75%~70%
Plan fitGrowth or ScaleGrowth or ScaleStarter or Growth

Pattern 1 — Hardware resellers

Multi-SKU distributors of equipment someone else built. Manufacturer documentation already exists; customers can't find it.

Before TruvyoAfter Truvyo
Support tech triages every ticket. 12-hour first-response on simple questions. Customer Agent answers in 1.4 s with citations. Techs only see escalations.
"Did you try a factory reset?" answered manually 40 times a week. Customer sees the reset procedure cited to the install-guide page before they open a ticket.
Vendor PDFs sit in a folder no customer reads. PDFs ingested into the Shared Library. Agent cites the page number on every answer.
No metric for which knowledge actually helped. Per-message feedback + nightly aggregation. Bad articles auto-bench. Gaps queue for the next research run.

Pattern 2 — Field service networks

Installer-heavy operations where Tier 1 is internal: field techs phoning HQ for specs and configurations.

Before TruvyoAfter Truvyo
Field tech hits an unfamiliar config; calls senior engineer. 15–25 minute interruption per call. Technical Companion on phone answers with citation to the manufacturer spec sheet.
Tribal knowledge in Slack threads. New techs ask the same questions every quarter. Same field knowledge served to every tech, immediately, with sources.
Customer waits for callback while tech researches. Job completes on first visit. Callback rate drops.
Onboarding new installers takes weeks of shadowing. Companion serves as institutional memory. Onboarding compresses to days.

Pattern 3 — Developer platforms

B2B SaaS with extensive API docs that customers do not read. Technical audience tolerates AI support better than any other buyer because they verify citations.

Before TruvyoAfter Truvyo
"Where do I find X in the docs?" tickets dominate the queue. Agent returns the doc section with citation. Customer follows the link, self-serves.
Senior engineers triage devrel inbox between shipping. Agent absorbs the boilerplate. Engineers focus on architecture questions.
SDK error codes have to be Google-searched on Stack Overflow. Agent cites the relevant API reference page on every error question.
Customer-facing changelog ignored. Changelog ingested into Shared Library. Agent surfaces relevant updates inline.

Who Truvyo is built for

If your support team is the bottleneck and the answers already exist somewhere — manuals, SOPs, Slack threads, your own knowledge base — you're our audience.

Hardware resellers + integrators

Multi-vendor distribution. Specialty IT. Network equipment. Satellite internet. IoT. Manufacturer docs become your first-line support layer.

Field service operations

HVAC, solar, telecom install, security systems, electrical. Technical Companion runs on a phone in the truck. Cited answers replace HQ phone calls.

Regulated industries

Medical devices, financial services, healthcare. "Every claim is cited and traceable" is a compliance feature, not a nice-to-have. Enterprise tier with HIPAA-compliant deployment.

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