Work arrives ready
Channel, customer, SLA, and intent
Zild agent management platform
Run service, sales, voice, documents, and back-office work with policy, human validation, and visibility in one place.
Platform control
Admin keeps the operating layer visible: active agents, connected channels, AI providers, queues, roles, policy states, usage, and budget health.

Managed agent work
Most AI initiatives stall between pilot and daily work. Zild is built for the middle layer: the policies, queues, evidence, validation points, and feedback cycles that make agents manageable in production.
Each run leaves ownership, evidence, and clear signals for the next round.
Channel, customer, SLA, and intent
Action, confidence, policy, and cost
Reason, owner, and next action
Outcome, QA note, cost, and escalation reason
Trends, coaching, and new policy
Production workflow
The request enters through WhatsApp, Assist handles safe work, the team takes exceptions, and the history is ready for QA.

Where to start
Use the first deployment to prove the operating path: request, policy, validation, evidence, and improvement.

For WhatsApp, chat, email, and SAC teams with repeated requests, SLA pressure, policy checks, and human validation.

Qualify leads, answer routine objections, schedule next steps, and keep CRM updates attached to the conversation.

Answer, qualify, route, transfer, and keep transcript evidence attached to the call outcome.

Classify attachments, extract fields, request missing data, and send risky records to human validation.

Review transcript-backed QA, coaching signals, exceptions, and proof of what changed.

For lead enrichment, document processing, CRM cleanup, pipeline data, or a playbook specific to your operation.
Control and evidence
Zild is designed for the moments where AI cannot be a black box: policy criteria, escalation paths, transcript evidence, permissions, QA, cost visibility, and operational ownership.
Low confidence, policy risk, SLA pressure, or high-value customer context.
The person enters with transcript, summary, customer state, and suggested next action.
Decision, outcome, QA note, cost, and follow-up remain searchable after the work.
Confidence, policy, SLA, and risk conditions bring a person in with context intact.
Every interaction leaves transcripts, decisions, outcomes, and review signals behind.
Leadership can see performance by agent, channel, department, and workflow.
We'll review your use case, channels, systems, and operating pressure, then show how Zild can launch the first measurable workflow with control.
Start a conversation on WhatsApp. We typically respond within minutes.