
Aria
Every candidate, interviewed live.
An AI interviewer that runs structured technical and behavioural screens for every applicant — engineers, clinicians, analysts, site leads — in 50+ languages, in real time.
- Adaptive follow-ups that probe depth, not keywords
- Industry rubrics: IT, healthcare, finance, construction
- Frontier-grade proctoring and anti-cheat detection
- Scored reports and recordings you compare side by side
- Multi-language support in 50+ languages
- Candidates in 150+ countries, top 1% pass rate

Hello! I'm Aria, Think5's AI interviewer. Welcome, I'm excited to get to know you. Could you briefly introduce yourself?
- 1,000+
- Daily interviews
- 150+
- Countries
- 50+
- Languages
- 1%
- Acceptance rate
Nexus
The right person, on the right role, in 48 hours.
A matching engine that pairs candidates with roles on verified skills, Aria scores and availability — across startups, enterprises and AI labs.
- Skill-to-role matching on interview evidence, not keywords
- Credential and licence verification per industry
- Comp benchmarks and availability built into the shortlist
- 24–48 hour shortlist turnaround
- Continuous quality scoring from real hiring outcomes
Matches · Senior Backend Engineer
Ranked by fit- PN
Priya Nair
Staff engineer · ex-Stripe · Berlin
96Aria94 - DK
Daniel Kim
Senior backend · fintech · remote
93Aria91 - AO
Amara Okafor
Platform lead · payments · London
90Aria89 - LM
Lucas Meyer
Backend · distributed systems · Munich
88Aria87
Match rationale · Priya Nair
Weighted on the role brief · updated 2m ago
- Skills, verified by Aria96
- Experience fit92
- Compensation alignment88
- Availability & location100
- Aria interview
- 94 · system design, depth
- References
- 2 of 2 complete
- Comp band
- $195–220k · inside band
- Start
- 4 weeks · notice served
Sourcing · live
- 48h
- To shortlist
- 4
- Core industries
- 100+
- Domains covered
- 99.7%
- Quality score
Forge
Expert intelligence, shipped as training data.
The data operations platform behind our AI training business: it turns the vetted expert network into RLHF, SFT, evaluation and red-teaming datasets for frontier labs.
- RLHF data pipelines for frontier models
- Supervised fine-tuning (SFT) workflows
- Red-teaming and safety evaluations
- Vision-language model (VLM) training data
- Multi-modal dataset creation
- Managed QA and delivery pipelines
RL environment · Clinical reasoning
Held-out eval- 1GPT-572.4%+3.1
- 2Claude Opus 4.770.9%+2.6
- 3Gemini 3 Pro66.2%+1.8
- 4Open-weights baseline51.7%—
Run details · Batch 4471
DeliveringItems
3,120
QA pass
99.7%
Agreement
0.91
Experts
48 MDs
Expert QA · items 2,801–2,896
pass · review · flag
Throughput · items / hr
412
Expert QA · live
reviewing now · 3 of 3 must agree
- 10M+
- Data points
- 99.7%
- Quality score
- 24/7
- Operations
- 6+
- Data modalities
RLHF
Reinforcement learning from human feedback
VLMs
Vision-language training data
Reasoning
Complex logical reasoning datasets
Multi-modal
Cross-modal understanding data
SFT
Supervised fine-tuning pipelines
Red teaming
Safety and adversarial testing
Ready when you are
See the platform in action.
Talk to our team about expert talent, custom data operations or an enterprise partnership.