Run support with scoped AI agents.

Pagerox helps teams connect the systems support already depends on, bind each agent narrowly, ground answers in real knowledge, and improve from live conversations without losing operational visibility.

Integrations

Connect the systems your team already uses.

Pagerox is designed to sit between support work and the tools that explain it. The platform can connect communication surfaces, engineering context, knowledge sources, and data access without flattening everything into one broad agent.

Slack

Communication

Teams

Communication

Discord

Communication

Telegram

Communication

GitHub

Engineering context

Linear

Engineering context

Notion

Knowledge source

Google Drive

Knowledge source

Supabase

Data access

Platform

What Pagerox actually does inside a support organization.

The product is built around four layers: scoped agents, grounded knowledge, reviewed learning loops, and the operational tooling teams need to roll those pieces out safely.

Keep every agent inside the right support boundary.

Pagerox is built around narrow, purpose-fit agents instead of one broad assistant. Teams can bind each agent to the exact channels, repos, docs, and systems it should use.

Shared organization credentials with agent-specific bindings
Slack channels and system access picked per agent
Safer rollout because every lane stays understandable

Workflow

How the support loop comes together.

Pagerox is strongest when teams connect shared systems once, scope each agent deliberately, and then refine behavior from the real support conversations they are already handling.

01

Connect shared systems at the organization level.

02

Bind the right channels, repos, docs, and schemas to each agent.

03

Ingest knowledge through manual entries, URLs, files, and connected sources.

04

Test in the playground and inspect traces before pushing more load.

05

Review learnings and improve support behavior from live traffic.

Agent bindings

Connect once at the organization level, then bind narrowly.

Pagerox separates shared integration ownership from agent access. That means support teams can reuse the same Slack, GitHub, Notion, Drive, and Supabase connections without giving every agent the same surface area.

Organization-level integration model
Agent-specific channel, repo, doc, and schema access
Easier rollout across multiple teams
Grounded answers

Knowledge ingestion, retrieval, and support context live together.

The platform already supports manual knowledge, URL crawl, file upload, embeddings, and retrieval. That lets Pagerox answer with the right context instead of defaulting to generic support language.

Manual, URL, and file ingestion built in
RAG retrieval against chunked knowledge
Support-case classification and context shaping in the AI layer
Traceability

Test, inspect, and tune before you widen support load.

Pagerox gives teams a playground, traces, analytics, and feedback views so support can see how an agent behaves before pushing more real conversations through it.

Playground for product-side testing
Agent performance, latency, and feedback signal
Trace surfaces for tools, context, and applied learnings
Warm-up and learnings

Turn live support work into reusable support configuration.

Pagerox can warm up from Slack support channels, draft support playbooks, propose learnings, and help teams convert repeated work into a cleaner operating model.

Slack channel warm-up flow
Draft playbook notes and entity patterns
Reviewable learnings instead of silent prompt drift

Trust by design

Security, integrity, and operating discipline show up in the workflow itself.

Pagerox should feel safer as teams widen rollout, not harder to reason about. That is why the product leans on narrower access, grounded answers, reviewable learnings, and visible usage.

Scoped access
Agents can be limited to the exact channels, systems, and knowledge surfaces they should use.
Traceable answers
Playground traces, logs, and analytics make it easier to understand why an answer happened and whether it is helping.
Visible usage
Agents, interactions, knowledge items, and members are all tracked inside the product so growth stays observable.

FAQ

Questions teams ask before they start.

These are usually the deciding questions for teams evaluating whether Pagerox fits their support model.

What makes Pagerox different from a generic support bot?

Pagerox is organized around scoped agents, shared organization integrations, grounded knowledge retrieval, reviewed learnings, and operational analytics. The product is built for support operations, not just conversational output.

Can teams start with one narrow rollout first?

Yes. The platform is a strong fit for starting with one support lane, one agent, and one clear set of sources and channels before expanding to more surfaces.

How do learnings work?

Pagerox can turn resolved conversations into candidate facts, corrections, preferences, patterns, and escalations. Teams can review those learnings and decide what should stay active.

What kinds of systems can Pagerox connect to?

Today’s codebase already supports communication surfaces, engineering systems, knowledge sources, and Supabase-based data access, with organization-level connection ownership and agent-level bindings.

Next step

Start with one narrow support lane, then expand with confidence.

Pagerox works best when teams begin with one real support surface, one grounded agent, and one clear operating model for how that lane should behave.