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.

Developer customers don't want empathy. They want your logs.

When developers report SDK errors, API regressions, or integration failures, they've already read your docs and tried debugging. They need the data they can't access — your internal logs, deploy history, and bug tracker. Altor pulls it all in 2 minutes.

Developer tool tickets that drain engineering time

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

•"SDK v4.2 crashes on React 19 with a hydration error" — known incompatibility, or a new regression introduced in the latest patch?
•"GraphQL subscriptions disconnect every 30 seconds in production" — WebSocket timeout config, load balancer idle timeout, or a known issue with your gateway?
•"Rate limit headers show 1000/min but I get 429 at 600 requests" — shared rate limit across API keys, or a counting bug in the middleware?
•"Batch API returns partial success but no indication of which items failed" — by design, a serialization bug, or a payload size edge case?

What Altor queries for developer tool companies

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

•ClickHouse / application logs — per-customer request patterns, error rates by SDK version, latency by endpoint
•GitHub — SDK release notes, breaking changes, compatibility matrix, open issues matching the report
•Linear — known bugs for this SDK version, regression tracking, priority and ETA
•API gateway metrics — rate limit counters, throttle events, per-key vs. per-org limits
•Documentation — version-specific migration guides, deprecation notices, known limitations

20-45 min

typical manual investigation for a developer ticket

< 2 min

Altor's median investigation time

$80-200K

annual cost per support engineer on manual investigation

3 weeks

from kickoff to full deployment

"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 developer tool companies are the ideal fit

Three traits make investigation automation especially effective for devtools: developer customers who expect technical depth and will churn without it, high ticket volume driven by integration complexity across many SDK versions, and well-structured API log data that Altor can query precisely.

Your support team is already technical. The bottleneck isn't skill — it's time. Twenty minutes per ticket checking the same systems in the same order. Altor runs that workflow in 2 minutes.

Altor for AI infrastructure companies API error investigation 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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