What is an AI services company?

An AI services company builds, deploys, and operates production AI systems for businesses. Unlike AI consultants (who produce strategy documents) or AI implementors (who hand off at launch), an AI services company stays accountable for the system working and improving over time. Altor builds AI systems that connect to your production tools and automate specific workflows — live in 3 weeks.

How much does it cost to build an AI agent?

Custom AI agent development costs $10K–$75K for a single-workflow production deployment, plus $1K–$5K/month for ongoing maintenance. A simple agent connecting to 1-2 systems costs $10K–$25K. A complex agent connecting to 5-6 production systems costs $40K–$75K. Most deployments go live within 3 weeks.

Is there software that can reduce support escalations?

Yes. Software that automatically investigates support tickets by querying production systems (logs, bug trackers, billing, recent deploys) gives frontline agents the context they need to resolve tickets without escalating. At Portkey, this approach reduced investigation time from 45 minutes to 2 minutes and eliminated the information gap that causes most escalations.

How long does AI deployment take?

A focused single-workflow AI deployment typically takes 2-4 weeks from kickoff to first live investigation. Week 1: stack audit and integration planning. Week 2: read-only connections live, first investigations on real data. Weeks 3-4: playbooks tuned, team trained, system handed over.

What is production AI?

Production AI is an AI system that operates continuously in a live business environment, handling real data and real users — held to the same reliability standards as any other production software. This is different from pilot AI (which runs in controlled environments) or demo AI (which shows capability without handling real workflows). 67% of enterprise AI projects fail to reach production.

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.

n8n Workflow Automation

n8n workflow automation is the use of n8n to orchestrate API calls, condition branches, database queries, and message handoffs across multiple systems without writing every step as custom backend code. Teams use it to connect help desks, CRMs, billing platforms, internal tools, and LLM services into event-driven workflows. It is especially useful for support operations because a ticket can trigger enrichment, severity checks, bug search, stakeholder alerts, and response drafting inside one graph-based execution path.

Why it matters for B2B support

n8n is attractive when support teams need operational speed without waiting for a full platform team to ship every integration. The tradeoff is that workflow reliability still requires proper credentials handling, retries, observability, and version control, especially when one workflow touches customer-facing systems or production data.

How Altor helps

Altor can sit inside an n8n flow as the investigation layer, pulling evidence from 6 production systems so the workflow returns diagnosis, not just routing metadata.

FAQ

When is n8n better than writing a small service?

When the work is mostly orchestration across existing APIs and needs fast iteration by ops teams. Custom services make more sense when the logic, volume, or compliance needs outgrow a workflow graph.

Can n8n handle support workflows safely?

Yes, if teams manage credentials, audit runs, and failure handling carefully. The risk comes from weak operational discipline, not from automation itself.

Related terms

Webhook AI Agent Ticket Triage

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