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. No minimum commitment. We'll scope pricing during the demo based on your ticket volume and systems.

Your customers don't file FAQ tickets. They file investigations.

AI infrastructure tickets are about API routing failures, model fallback chains breaking, gateway latency spikes, and token usage discrepancies. These aren't questions a knowledge base can answer — they require pulling live data from your customer's actual API logs, configs, and billing.

Ticket patterns unique to AI infrastructure

If you're building an AI gateway, observability platform, or prompt management layer — your support tickets are fundamentally different from typical SaaS. Your customers are developers pushing production LLM traffic through your platform. When something breaks, they need root causes with evidence.

•"Requests to Claude are failing but GPT-4 works" — routing config, provider outage, or fallback chain not triggering?
•"Model fallback isn't activating when OpenAI times out" — threshold config issue, or a gateway bug introduced in a recent deploy?
•"Token counts on our invoice don't match our logged usage" — tracking discrepancy from prompt caching, or a billing pipeline bug?
•"Latency doubled on our production routing requests" — your gateway overhead, the provider's response time, or a DNS issue?
•"Our custom metadata isn't being passed through to the model provider" — request transformation bug or API version mismatch?

What Altor investigates for AI infra teams

For AI infrastructure companies, Altor connects to the specific systems where gateway and routing data lives:

•ClickHouse / your analytics DB — request logs per model provider, routing decisions, fallback triggers, latency per hop
•Linear / Jira — known gateway bugs, routing issues, provider compatibility problems
•Stripe — token-based billing, usage tiers, overage calculations against actual logged tokens
•GitHub — gateway deploys, routing config changes, SDK version releases
•StatusPage / PagerDuty — upstream provider outages (OpenAI, Anthropic, Azure, AWS)

2 min

median diagnosis at Portkey — an AI gateway handling billions of requests

200+

tickets diagnosed across gateway routing, latency, and billing patterns

70%

of Portkey's support volume covered by 3 investigation playbooks

3 weeks

from kickoff to full deployment at Portkey

"Our tickets are investigations — "why is this model routing failing for this customer?" Nobody else could even attempt to answer that automatically. Altor can because it actually queries our ClickHouse logs."
— Engineering lead, Portkey

Why AI infra is the ideal fit for Altor

AI infrastructure companies have three traits that make investigation automation especially effective: highly technical tickets that always require multi-system data, well-structured request logs in systems like ClickHouse that Altor can query precisely, and engineering-heavy support teams that value root causes over templates.

Portkey was Altor's first deployment. The patterns built there — provider routing failures, latency spike diagnosis, token billing cross-referencing — transfer directly to other AI infrastructure companies.

How Portkey uses Altor — full case study Altor for API-first developer tools API error investigation walkthrough

Your stack looks like Portkey's. See what Altor finds.

We'll connect to your API logs, bug tracker, and billing system and investigate a real ticket from your queue.

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