How is Altor different from a docs chatbot?

Docs chatbots answer 'how does this work?' from your knowledge base. Altor answers 'why is this broken for this customer right now?' by querying their actual API logs, checking your bug tracker, and verifying their billing status — across 6+ systems in under 2 minutes.

How is Altor different from our support platform?

Pylon, Plain, Zendesk — they route and manage tickets. Altor investigates them. We plug into your existing support tool as the investigation layer. You keep your workflows, we add the diagnosis.

Will Altor take actions without asking?

Not by default. Altor starts as a read-only investigator — it surfaces a diagnosis for your team to review. You control which action types graduate to auto-approval. Destructive actions are never automated.

What if our stack isn't listed?

If an API exists for your system, we can integrate it. The architecture composes tools — it doesn't hardcode connectors. We've yet to encounter a B2B stack we can't connect to.

What does Altor pricing look like?

Usage-based — you pay per investigation, not per seat. Pricing is quoted in USD ($) with no minimum commitment. We'll scope pricing during the demo based on your ticket volume and systems.

Support Quality Score

Support quality score is an internal measure of how accurate, complete, and policy-compliant support responses are. For technical teams, quality means the answer was not only polite, but actually correct and backed by evidence from the customer’s systems.

Why it matters for B2B support

B2B support quality drops when agents rely on guesswork or generic playbooks for technical problems. A response can sound professional and still be low quality if it misses the real cause of the issue.

Key benchmarks

85%+

target internal QA score for mature teams

2–5

review criteria often used in support QA rubrics

1 source

minimum evidence expected in technical answers

70%

quality risk when agents answer before investigating

How Altor helps

Altor improves quality scores by giving agents structured diagnostic findings they can review before sending. That reduces speculative replies and increases consistency across the team.

FAQ

What lowers support quality scores most?

Inaccurate technical answers, missing next steps, and responses that sound polished but do not address the actual issue.

How do teams improve quality at scale?

Use clear QA rubrics, give agents faster access to evidence, and reduce the need to guess when diagnosing customer issues.

See Altor investigate a real ticket

We connect to your systems and diagnose a real ticket in 2 minutes during US hours.

Book a Demo