Colab’s AI-Driven Insights Repository ingests reports, videos, transcripts, and raw metrics, then uses natural-language search and pattern recognition to surface recurring pain points, track UX KPIs, and inform roadmaps without manual data wrangling.
Research knowledge too often lives in forgotten slide decks and unindexed video libraries, causing expensive duplication and slow decisions. Colab’s AI-Driven Insights Repository solves this by funneling every asset from your yearly usability, eye-tracking, and accessibility engagements into a secure, queryable platform. Advanced language models automatically tag themes, sentiments, and severity levels, while visual analytics expose patterns across projects, personas, and time.
Stakeholders can ask plain-language questions—“Show me navigation issues in mobile banking”—and instantly retrieve clips, quotes, and heatmaps. All data resides on encrypted servers within Saudi Arabia, meeting PDPL and GDPR requirements. Annual plans include onboarding, continuous model tuning, and priority support, ensuring your organisation extracts compounding value from every research investment without additional headcount.

Align test objectives with business KPIs and personas.

Source vetted participants matching demographics and device criteria.

Capture tasks, emotions, and eye-tracking data seamlessly.

Receive severity-ranked report and recordings within three to five days.
Drag-and-drop files or bulk import via our secure portal.
Yes, each plan unlocks a storage quota aligned to study volume.
Absolutely—upgrade tiers anytime; unused capacity never expires.
PDFs, DOCX, MP4, CSV, and most common research outputs.
Yes—Arabic speech-to-text and sentiment models are included.
Only authorised users you assign; role-based permissions control visibility.
Download highlight reels, annotated clips, and trend charts in PPTX.
Data is encrypted at rest and in transit, hosted on PDPL-compliant servers.
Similarity alerts notify you when proposed objectives match existing evidence.
Roadmap integrations push tagged issues directly into backlog tools.
Yes—researchers can override or refine AI labels anytime.
Most teams are fully operational within one week of kickoff.