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.

Contact Volume

Contact volume is the total number of support interactions received across all channels, including email, chat, phone, and in-app messaging, within a measurement period. It is the input signal for every staffing and queue-management decision.

Why it matters for B2B support

Contact volume forecasting drives support headcount, scheduling, and escalation coverage. In B2B support, volume is highly predictable when teams use the right leading indicators: product releases often spike ticket volume by 20–60% in the following 72 hours, new onboarding cohorts generate about 3× the ticket rate of mature customers, and Q4 enterprise evaluation season often increases demand by 15–25%. Teams that ignore those drivers make reactive staffing decisions after burnout starts. At steady state, every 100 new enterprise customers usually adds about 35–55 monthly tickets.

Key benchmarks

3×

ticket rate from new customers (< 90 days old) vs. mature customers

20–60%

contact volume spike in 72 hours following a product release

35–55

monthly tickets added per 100 new enterprise customers at steady state

25%

Q4 volume increase for B2B SaaS serving enterprise buyers in evaluation cycles

How Altor helps

Altor makes contact-volume growth easier to absorb by reducing the work per ticket, especially on technical issues. That helps teams scale capacity without matching every volume increase with new headcount.

FAQ

What predicts contact volume best in B2B SaaS?

Release schedules, onboarding volume, customer mix, and renewal seasonality. Historical averages matter, but those forward-looking signals are what explain the spikes.

Why does contact volume matter beyond staffing?

Because it shapes SLA risk, queue depth, and escalation load. Underestimating volume means every downstream support metric gets worse at once.

See Altor investigate a real ticket

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

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