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.

How do I automate customer feedback analysis with LangChain?

Aggregate NPS responses, support tickets, and reviews, extract themes, and surface product insights weekly. Weekly digest of top themes, sentiment trends, and specific customer quotes delivered automatically to product team Slack.

What are the steps to set up customer feedback analysis automation?

Scheduled trigger collects feedback from all sources Then: AI clusters by theme and scores sentiment Then: Top 5 themes this week identified with supporting quotes Then: Digest posted to Slack with links to source conversations

How long does it take to automate customer feedback analysis?

With Altor, most workflows go from audit to live production in 3 weeks. DIY with tools like n8n or Make typically takes 2-6 weeks depending on integration complexity.

Automation guide

How to Automate Customer Feedback Analysis with LangChain

Aggregate NPS responses, support tickets, and reviews, extract themes, and surface product insights weekly.

The problem

Product teams have feedback scattered across Intercom, G2, AppStore, NPS surveys, and support tickets. Nobody synthesises it regularly.

The outcome

Weekly digest of top themes, sentiment trends, and specific customer quotes delivered automatically to product team Slack.

The tool

LangChain — Python/JS framework for building LLM applications.

How it works — step by step

1
Scheduled trigger collects feedback from all sources
2
AI clusters by theme and scores sentiment
3
Top 5 themes this week identified with supporting quotes
4
Digest posted to Slack with links to source conversations

About LangChain

Python/JS framework for building LLM applications. Best for developers building custom AI agents and RAG pipelines.

Strengths

✓ Full control
✓ RAG pipelines
✓ Agent frameworks
✓ Vector store integrations

Pricing

Open source. LangSmith observability from $39/month.

Documentation ↗

Want this in production?

Altor builds customer feedback analysis automation for US B2B companies.

We don't hand off code and disappear. We connect to your live systems, ship to production in 3 weeks, and stay until the system delivers measurable impact. Weekly digest of top themes, sentiment trends, and specific customer quotes delivered automatically to product team Slack.

Email us your workflow →

How it works — step by step

About LangChain

Related guides

Altor builds customer feedback analysis automation for US B2B companies.