Agent evaluation
Structured human review for answer quality, escalations, policy adherence, and the edge cases your metrics miss.
AI QUALITY OPERATIONS / NEPAL
Make customer-facing AI answerable.
Blueheaven Nepal gives US AI and customer-experience teams a disciplined human layer for evaluation, QA, and continuous improvement.
FIELD NOTE / 001US ↔ NEPAL
THE OPERATING QUESTION
Where does your agent lose the thread?We turn the answer into an actionable review loop.THE BLUEHEAVEN DIFFERENCE
Not a queue of anonymous tasks.
An accountable quality layer.
AI products improve when human judgment is operational: clear instructions, calibrated reviewers, measured agreement, and a feedback loop your product team can use.
Our Nepal delivery team works within a defined operating boundary—so quality can scale without losing control of customer data, brand voice, or release standards.
WHAT WE OPERATE
Focused services for teams that have moved beyond prototype mode.
RAG readiness
Knowledge-base preparation, retrieval relevance checks, citation review, and regression sets built around real workflows.
Voice & CX QA
Transcript review, intent coverage, handoff analysis, and release validation for customer-facing AI agents.
EXAMPLE PILOT SHAPES
Illustrative pilot structures—not client case studies. Each shows the evidence and handoff a team can expect from an initial engagement.
ILLUSTRATIVE PILOT
Support agent QA baseline
Define high-risk intents, score an agreed review set, and deliver a prioritized error taxonomy with clear examples for the product team.
ILLUSTRATIVE PILOT
RAG answer & retrieval review
Test retrieval relevance, grounded answers, and citation behavior across an agreed scenario set—then turn the findings into a practical regression plan.
ILLUSTRATIVE PILOT
AI handoff & escalation audit
Review customer conversations around handoffs, policy-sensitive moments, and escalation thresholds to document actionable release gates.
SAMPLE DELIVERABLE / PDF
See the shape of the work
before you commit.
An anonymized example of an AI agent QA pilot report: review framing, an illustrative error taxonomy, and the handoff a product team receives.
This is an illustrative template, not a client report. It contains no customer data and no claimed client results.
Open the sample reportHOW DELIVERY STAYS IN BOUNDS
Quality work belongs
inside a controlled system.
Customer-controlled data
Your cloud tenant, your access rules, your audit trail.
Human review where it matters
Calibrated reviewers, golden sets, and documented escalation paths.
A measured handoff
Defined acceptance criteria, clear reporting, and a practical next release.
DEFAULT DELIVERY POSTURE
Customer-hosted workspace · role-based access · no unapproved subcontracting · documented QA · production data only by explicit agreement.
PILOT / 02 WEEKS
START SMALL. LEARN FAST.
A defined sprint,
not an open-ended promise.
We begin with a bounded workflow, a review rubric, and a measurable output: an evaluation set, a failure-mode report, or a clear path to a recurring QA program.
YOU LEAVE WITH
- Calibrated scoring criteria
- A prioritized error taxonomy
- Evidence for your next release decision
START THE CONVERSATION
Bring one difficult workflow.
Tell us where reliability matters most. We will return with a practical pilot shape—not a generic staffing proposal.
Typical responseWithin one business day