Primary buyers
- Head of BPO operations
- Shared services director
- CX or contact center lead
- QA, compliance, and workforce leaders
Back to use cases
BPO and shared services
AI workflows for BPO support, QA, and back-office operations.
Agentic AI helps BPO teams handle high-volume work with faster routing, stronger quality control, better SLA visibility, and human review where judgment is required. The AI supports service representatives and supervisors; it does not replace their judgment.
What it does
Turns high-volume service work into controlled, measurable workflows.
Faundra Labs builds AI workflows that classify incoming work, summarize context, recommend actions, draft responses, update systems, review quality, and escalate exceptions according to each client program's rules and SLA commitments.
Who it helps
Built for delivery leaders who need scale without losing control.
Not ideal for
- Unstable processes without defined playbooks
- Workflows where the AI would be expected to make final sensitive decisions without supervisor approval
- Teams that cannot provide system access, policies, or sample work
Benefits
Where value shows up.
Lower handling time
Give support representatives the customer context, policy answer, and next best action before they start from scratch.
Higher quality consistency
Review conversations, tickets, and case notes against the same client-specific QA rubric.
Better SLA control
Monitor queue aging, urgency, backlog, and breach risk so team leads can act earlier.
Faster onboarding
Use guided workflows and live knowledge support to help new representatives reach productivity sooner.
Examples
Practical deployments.
AI ticket triage
Classifies emails and tickets, detects urgency, summarizes the issue, routes to the right queue, and suggests resolution steps.
Representative assist
Reads customer history, knowledge base, policies, and system data to draft responses and recommend the next action for service representatives.
AI QA review
Scores calls, chats, and tickets against rubrics, detects compliance risk, and prepares coaching notes for team leads.
Back-office workflow automation
Extracts data from forms, validates against rules, flags missing items, and prepares cases for human approval.
Flow
How the AI workflow works.
Intake
Read permitted tickets, emails, transcripts, forms, CRM records, knowledge articles, and client playbooks.
Recommend
Classify the request, apply client rules, identify missing information, and recommend the next best action.
Assist
Draft responses, update approved systems, trigger follow-ups, score quality, and escalate exceptions to supervisors.
Best first pilot
Start with one queue and one measurable SLA.
A strong first deployment is email or ticket triage for one client program, paired with AI recommendations for support representatives and QA review on the same queue.
- Inputs: 30 to 60 days of tickets, playbooks, QA rubric, SLA rules, and resolution policies.
- Success measures: triage accuracy, handling-time reduction, QA coverage, escalation quality, and SLA breach prevention.
- Human approval: required for account changes, refunds, policy exceptions, and compliance-sensitive replies.