Built on PlantoOS

Customer Support Copilot

Support acceleration with conversational memory, knowledge retrieval, and governed response assistance.

Why support teams lose resolution speed

  • Support agents spend too much time searching fragmented internal documentation.
  • Context from past conversations is often lost across channels and handoffs.
  • Teams need response assistance without sacrificing accuracy and governance.
  • Upsell and retention opportunities are missed during support interactions.

What Customer Support Copilot provides

AI-assisted responses

Provide support agents with context-aware suggested replies in real time.

Support CopilotTKT-8847
active

Live Support Chat

Acme Corp · Enterprise Growth plan · TKT-8847

CustomerOur API calls keep timing out since the migration last week.
AgentI can see the migration history on your account. Let me check the gateway timeout profile.
CustomerIt works fine for small payloads but fails on batch operations.

AI Suggestions

Share gateway timeout configuration steps

Confidence: 94%

Suggest token rotation for batch endpoints

Confidence: 87%

Offer diagnostic script for latency profiling

Confidence: 82%

Ticket

PriorityHigh
SLA4h remaining
ChannelChat
AgentSarah K.

Conversation memory

Retain customer context across channels and support handoffs.

Support CopilotTKT-8847
active

Customer History

Acme Corp · Full interaction timeline

Interaction Timeline

Feb 02Billing dispute — credits appliedEmail
Feb 19Gateway migration supportSlack
Mar 05SSO configuration assistanceChat
Mar 08Batch API timeout escalationChat

Auto-Injected Context

Customer migrated gateway infrastructure on Feb 19. Current issue likely related to post-migration batch endpoint configuration. Context reused from 2 prior sessions.

Account Info

PlanEnterprise Growth
MRR$18.4k
CSAT4.6 / 5
ChannelSlack Connect
Infraus-east gateway

Instant knowledge retrieval

Fetch relevant internal docs and runbooks directly in active tickets.

Support CopilotTKT-8847
active
gateway timeout after migration batch endpoint

Knowledge Results

DocumentTypeMatch
Gateway Migration RunbookRunbook98%
Timeout Policy ConfigurationConfig94%
Token Rotation ChecklistChecklist87%
Regional Latency TroubleshootingGuide81%

Search Stats

Indexed12,480
Searched1.1s
Results4
Scopeinternal

Upsell opportunity detection

Surface expansion signals based on customer issues and intent.

Support CopilotTKT-8847
active

Revenue Signals

Expansion opportunity detected from support interactions

Opportunity Indicators

Mentions SLA concerns frequently

High intent for priority support

Asks about proactive monitoring

Interest in observability add-on

Evaluating multi-team rollout

Expansion to 3+ teams likely

Revenue Signal

$42k ARR expansion

Recommend Enterprise Priority Support offer

Confidence

88%

Account

Current ARR$221k
Teams8
Usage trend↑ 34%
NPS72

Policy-bound agents

Capability enforcement ensures autonomous systems operate within explicit boundaries.

Governance Flow

Policy-bound agent execution ensures autonomous systems operate within boundaries.

Policy Layer
Agents
Capability Policies
Approved Tools
Enterprise Systems
Denied — policy block

Autonomous systems require explicit boundaries.

Where it sits in the stack

PlantoOS Architecture

The stack relationship between apps, agents, runtime, and systems.

Applications

Products and workflows

Agents

LLM-powered autonomous units

PlantoOS Runtime

Execution · orchestration · control

Capability Layer

Policy enforcement and tool access

Medhara Core

Memory · governance · lineage

Enterprise + Public Systems

Databases, APIs, infrastructure

A new compute layer for systems operated by agents.

Key workflows

How data flows through the system in typical usage patterns.

Workflow 1

Input

New support conversation

Core Process

Retrieves relevant knowledge and prior customer context

Output

Faster first-response with accurate grounding

Workflow 2

Input

Live response drafting

Core Process

Generates policy-bounded suggestions for support agents

Output

Consistent high-quality responses with agent control

Workflow 3

Input

Resolution and follow-up

Core Process

Summarizes interaction and flags expansion opportunities

Output

Structured case memory and upsell signals

Measured outcomes

↓ 20–35%

Average resolution time

↑ 18–30%

First-contact resolution

↑ 10–20%

Expansion opportunity capture

Indicative ranges from internal benchmarks and early deployments; results vary by workload, model, and infrastructure.

How it integrates

SDK-first integration — governed from the first line of code.

1

Connect channels

Integrate ticketing, chat, and CRM context

2

Configure policies

Set response boundaries and escalation rules

3

Assist agents

Enable live suggestions and conversation memory