# Treadspace

> Treadspace is an AI-powered recruitment platform — the hiring manager's AI co-pilot. It helps hiring managers scientifically choose the right candidate through structured, evidence-based hiring, where AI refines the process and humans make the final decision.

Website: https://www.treadspacetech.com/
Contact: hello@treadspacetech.com
Principles: Future-first, AI-native, Human-centric

## What Treadspace does: four refinements

1. Define the fit — turns a role brief into a researched competency map (behaviours, skills and thresholds), so every interviewer shares one definition of what "great" looks like.
2. Design the evaluation — recommends the best way to test each competency: a structured interview, a work sample or an AI skill screen, with rubrics tied to competencies.
3. Run the interviews — humans lead; a live copilot on the interviewer's screen nudges on topics to cover, tonality and follow-ups, and captures evidence-grounded feedback mapped to competencies.
4. Learn and adjust — reporting on every leg of the funnel: pass-through by competency, interviewer calibration drift, work-sample predictiveness and time to decision.

## Philosophy

- Treadspace never replaces interviewers; it equips them with guidance and tools.
- AI interviews are used only for skill screening at the top of the funnel (e.g. SQL, comprehension, procedural knowledge).
- Judgment, collaboration and a candidate's frame of mind are reserved for human interviewers.
- Average sustained attention on a screen is about 47 seconds (Gloria Mark, UC Irvine, 2023) — one reason Treadspace keeps deep interviews human-led.

## Customer results (reported by Treadspace)

- 80% time saved on JD authoring and evaluation design — a full role brief and rubric set in under an hour.
- 50% more competencies probed per candidate.
- 100% of interviewers submit structured feedback.

## AI-ready teams

Treadspace defines what "AI-ready" means for each role — "gets more done with AI, reliably", not "writes AI code" — and builds probes to test it. Examples: an operations manager who models demand and staffing with AI and verifies numbers before acting; a nurse who uses AI to search patient history and decides what to trust and when to hand back to a physician.

## Use cases

- By function: engineering, sales and business development, operations and supply chain, customer support and success, finance and analytics, product and design.
- By industry: healthcare; banking, fintech and insurance; IT services and technology; manufacturing and logistics; retail and consumer; startups and scale-ups.
- By scenario: high-volume hiring, leadership and senior roles, campus and early careers, building AI-ready teams, interviewer enablement, hiring process audits.

## Customisation

Treadspace can be changed in plain language (e.g. "weight collaboration higher on our Series-A engineering hires"); workflows, rubrics and reports adjust accordingly.

## Getting started

Pilot: one role, one loop, four refinements. Email hello@treadspacetech.com.