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.

Zendesk routes tickets. Your engineers still investigate them manually.

Zendesk AI auto-tags, routes, and suggests articles. But when a customer reports 'latency spiked since yesterday,' someone still has to open ClickHouse, check Linear for bugs, and cross-reference Stripe billing. Altor automates that investigation layer.

Tickets Zendesk AI can't solve

These are the tickets that sit in queue until an engineer has time to investigate:

•"API response times doubled for our enterprise tier" — infrastructure bottleneck, query regression, or upstream provider degradation?
•"Our SSO integration broke after your last update" — config drift, OAuth token expiry, or a breaking change in the latest deploy?
•"Webhook delivery success rate dropped from 99% to 83%" — their endpoint failing, your delivery pipeline backed up, or a regional outage?
•"Billing shows 2M requests but our internal counter shows 1.4M" — double-counting bug, or a metering discrepancy in batch endpoints?

What Altor queries for Zendesk-integrated teams

Altor connects to the systems where your investigation data actually lives:

•ClickHouse / your analytics DB — per-customer request logs, latency percentiles, error rates by endpoint and time window
•Linear / Jira — open bugs matching ticket keywords, recent regressions, deploy-correlated issues
•Stripe — subscription tier, usage metering, invoice line items vs. actual logged usage
•GitHub — recent deploys, breaking change PRs, SDK version compatibility
•Zendesk ticket context — prior ticket history, account tier, escalation patterns

2 min

median investigation time vs. 25 min manual

systems queried per ticket — automatically

80%

of B2B tickets need investigation, not article lookup

changes to your existing Zendesk workflows

"Our tickets are investigations, not FAQs. Nobody else could even attempt to answer them automatically. Altor can because it queries our actual production data."
— Engineering lead, Portkey

Why Zendesk teams adopt Altor

Zendesk's AI handles routing and article suggestions — that covers maybe 20% of B2B technical volume. The other 80% sits in queue until an engineer manually checks logs, billing, and bug trackers. That's the 20-45 minute bottleneck per ticket.

Altor plugs into Zendesk as an investigation layer. Tickets that need diagnosis get investigated automatically. Your Zendesk workflows, macros, SLAs, and team structure stay exactly the same.

Altor vs. support platform AI API error investigation walkthrough Portkey case study

See Altor investigate a real ticket from your queue

We'll connect to your systems and run a live investigation. Your data, your ticket, diagnosed in 2 minutes during EST or PST hours.

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