High Tech & SaaS

# Search that ships as fast as you do.

Engineering teams waste hours finding internal docs. Customers abandon products when they can't find answers in your help centre. Keyspider fixes both, deployed in days, not quarters.

- Customer-facing docs and help centre search with AI answers
- Internal search across Confluence, Notion, GitHub, Jira, and Slack
- Onboard new engineers faster with unified knowledge search

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Keyspider Search
How do we handle rate limiting on the v2 API?

The v2 API enforces a 1000 req/min limit per API key. Exceeding this returns HTTP 429 with a Retry-After header. Use exponential backoff starting at 500ms.

API Reference v2.4 Engineering Runbook: Rate Limits
What is the onboarding flow for enterprise SSO customers?

Enterprise SSO onboarding involves: SAML 2.0 or OIDC config from the customer's IdP, a test tenant provisioned within 24 hours, and a 45-min technical setup call with Solutions Engineering.

Enterprise Onboarding Playbook Solutions Engineering: SSO Checklist
Why did the June 14 deploy cause elevated p99 latency?

Root cause: a missing index on the search_events table caused full table scans on queries with date filters. Fix deployed June 15 at 03:12 UTC. p99 returned to baseline within 8 minutes.

Incident Post-Mortem: INC-2847 Infrastructure Runbook
Sources: Confluence, GitHub, Jira, Notion, Slack⚡ 160ms
The challenge

## Information is your product. Losing it to poor search is expensive.

Fast-growing SaaS companies generate enormous amounts of internal knowledge — in Confluence, Notion, GitHub wikis, Slack threads, and Jira tickets. And customer-facing docs grow just as fast. Both suffer from the same problem: search that can't keep up. New engineers spend weeks finding things. Customers raise support tickets for answers already in the docs.

1

New engineering hires spend weeks rediscovering institutional knowledge

2

Support ticket volume is driven by customers who can't find answers in docs

3

Internal knowledge is fragmented across Confluence, Notion, GitHub, and Slack

4

Product docs go stale and internal search surfaces outdated results

The Keyspider solution

## AI search built for the pace of SaaS

Keyspider connects to every tool engineering and product teams already use — and surfaces the right answer without switching tabs.

### Customer docs & help centre search

Embed AI search in your documentation site so customers find answers without raising a ticket. With AI-generated summaries, they get the answer — not just a link to a page.

### Internal knowledge search

One search bar across Confluence, Notion, GitHub, Jira, and Slack archives. Engineers find the answer without posting in #general.

### Onboarding acceleration

New hires get a single place to ask questions about architecture decisions, processes, and tooling. Institutional knowledge becomes findable on day one.

### API & developer docs search

Semantic search across your API docs means developers find the right endpoint, parameter, or code example — even when they search in different terms to what you wrote.

### Real-time indexing

Docs updated in Confluence or GitHub are searchable within minutes. No overnight crawls, no stale results during active sprints.

### SSO & permissions

Integrates with your existing identity provider. Engineers see results for content their role can access. No over-sharing of sensitive architecture docs.

## What SaaS teams see with Keyspider

3×

Faster onboarding for new engineering hires

40%

Reduction in support tickets from docs search

2 weeks

Time to go live

< 200ms

Average search response time

## How SaaS companies use Keyspider

### Developer docs & API reference search

Technical documentation is dense and constantly changing. Keyspider's semantic search helps developers find the right endpoint, code example, or guide — even when they search in plain English rather than exact API terminology.

### Customer support deflection

Embedding AI search in your help centre means customers resolve issues themselves. Keyspider's AI-generated summaries give them the direct answer, not a list of pages to scroll through — reducing tier-1 support volume significantly.

### Internal engineering knowledge

Architecture decisions, runbooks, incident post-mortems, and technical guides are often in six different places. Keyspider searches all of them from one bar — so engineers stop re-asking questions that were answered last quarter.

### Product team operations

Product managers searching across Jira, Confluence, Figma annotations, and Slack for context on a feature can find everything in one place. Keyspider Workplace Search covers every tool in the product stack.

## Ready to give your users better answers?

AI Search, AI Assistant, and Workplace Search. Deployed in days, not months. See it live on your own content.

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