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.

Tiered Support Model (L1/L2/L3)

A tiered support model organizes support teams into levels: L1 (frontline agents handling initial contact), L2 (senior agents with deeper technical knowledge), and L3 (engineering teams handling the most complex issues). Each tier has defined scope and escalation paths to the tier above.

Why it matters for B2B support

The tiered model was designed for consumer support in the 1990s where L1 resolved most tickets with scripts. In B2B technical support, the model breaks down because 60–80% of tickets require investigation that L1 agents cannot perform — they lack access to production databases, API logs, and billing systems. The result: chronic escalation rates of 25–40% for technical B2B teams, with each escalation adding 45–90 minutes to resolution time and pulling engineers away from product work. Companies like Portkey found that their L1 agents were escalating not because they lacked knowledge, but because they had no way to query ClickHouse or Linear to diagnose the issue.

Key benchmarks

25–40%

typical escalation rate for B2B technical support teams using tiered models

45–90 min

added to resolution time per escalated ticket

60–80%

of B2B tickets that require investigation L1 cannot perform manually

3×

higher cost per ticket when escalated to L2/L3 vs. resolved at L1

How Altor helps

Altor eliminates the investigation bottleneck that forces escalation. L1 agents receive automated diagnoses, enabling them to resolve tickets that previously required L2 or L3.

FAQ

What is L1, L2, and L3 support?

L1 (Tier 1) handles initial contact and resolves simple issues using scripts and knowledge bases. L2 (Tier 2) handles escalations requiring deeper technical knowledge or system access. L3 (Tier 3) is usually engineering — handling bugs, outages, and issues requiring code-level investigation. In B2B SaaS, the boundary between L2 and L3 is often where 70% of resolution time is lost.

Does the tiered support model work for B2B technical support?

Poorly. L1 agents cannot investigate production issues, so 30–40% of tickets get escalated regardless of agent skill. The bottleneck is data access, not knowledge.

What is the alternative to tiered support?

Swarming (all agents handle all tickets) combined with investigation automation. When every agent has automated access to diagnostic data, the tier distinction becomes unnecessary.

How do you reduce L2/L3 escalations in a tiered model?

The highest-impact fix is giving L1 agents automated access to the same data L2 engineers use. When L1 can query your ClickHouse, Stripe, and GitHub automatically, they resolve 60–70% of tickets previously requiring escalation — without changing headcount or training programs.

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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