Knowledge Workers Spend 30% of Their Week Looking for Information. That's Structural.
Forrester research found knowledge workers in large organisations spend 30% of their time looking for data. IDC estimates this costs enterprises $14,000 per knowledge worker annually. For engineering teams, product managers, and customer success functions, this productivity tax compounds with every tool you add. SearchSense Workspace eliminates it. SearchSense Assist handles the customer-facing support surface area that grows with every feature you ship.

Already trusted by industry leaders
30%
of the working week lost to information retrieval
$14K
annual productivity cost per knowledge worker from poor enterprise search
1.8 hrs
per day spent searching and gathering information
35%
reduction in knowledge search time with structured AI search
The SaaS Knowledge Problem — Specific and Solvable
Every SaaS company above 50 people knows these failure modes. Every company above 200 is paying for them in engineer hours, onboarding time, and support headcount.

01
Knowledge is in too many places at once
Notion, Confluence, Slack, Jira, GitHub, Drive — partial context on every question, in six different tools.

02
Senior engineers answer questions that are documented
New hires interrupt senior colleagues for answers already written — somewhere they can't find them.

03
Incident response slowed by knowledge retrieval
Engineers spend the first 15 minutes of a P0 finding the runbook. That time is measured in downtime.

04
Support can't scale without headcount
Every new feature creates new support surface area. Without AI deflection, headcount scales linearly.

05
Product context is lost and rebuilt repeatedly
The Slack thread, Notion doc, and Jira ticket for any decision exist — but recovering all three takes hours.

06
Onboarding quality degrades as teams scale
By the 50th hire, onboarding relies on documentation quality — not on founder context. Search quality determines ramp speed.
Explore all products
AI-powered product discovery for technical catalogs — from 10,000 SKUs to 1 million. Exact match, attribute filtering, and merchandising.

AI knowledge search for sales and operations teams behind your portal. Find any spec sheet, pricing doc, or product PDF in under 10 seconds.

SaaS & Technology in Practice
Four scenarios reflecting the most common knowledge and support transformation patterns across engineering, product, customer success, and support functions.
Workspace returned the relevant runbook, last three incidents, and on-call channel in a single query during production.
New engineers found documented answers independently — senior interruptions fell 60%, time-to-contribution dropped 40%.
Assist handled setup, integration, and billing queries automatically — agents focused on edge cases requiring expertise.
Roadmap prep that previously required hours of archaeology completed in minutes using natural language Workspace queries.
