Proprietary, accurate data. Built for GenAI.
Delivered across modalities for the GenAI lifecycle, backed by the infrastructure, workflows, and security.
Frontier
AI Lab
Leading
Smartphone Maker
Major
Social Platform
Top GenAI
Assistant Maker
Leading
Search Engine
Leading Global
Ecommerce
Frontier
Robotics Studio
Iconic
Smart Eyewear
World-Leading
Creative AI Platform
Premium
Automotive AI
Top-20
US Mortgage Lender
Major
Crypto Trading Platform
Global
Banking-as-a-Service
Emerging
BNPL Fintech
Global
Card Issuer
Tier-1
FinCrime Portfolio
WHY THIS MATTERS
The forces reshaping AI
Six market forces putting AI at risk, and why operationalizing your data services matters now.
Open-source is catching up
1.70%
open-source AI now performs within 1.70% of top commercial models, down from 8% just a year ago.
Stanford AI Index 2025
Training AI on AI hurts quality
2X
models trained on AI-generated content lose quality fast, and degrade further with every generation.
Shumailov et al., Nature 2024
AI benchmarks are unreliable
42%
of recent AI evaluation results were inflated because test questions leaked into training data.
Balloccu et al., 2024
Most of the web isn’t English
~55%
of web content is in languages other than English. Most AI models are built English-first.
Common Crawl statistics
Copyright lawsuits are surging
166
active US lawsuits against AI companies, with over $50 billion in damages on the table.
AI Lawsuit Tracker, Oct 2025
PROVEN OUTCOMES
We operationalize at frontier scale
61%→ 84%
plausibility of medical claims, lifted across two RLHF cycles before 14-hospital deployment.
94.7%
Top-1 accuracy on a spatial-VR hand-tracking model across 16 classes and 20 markets.
50%
faster model development on an 8-language virtual-assistant speech program.
99.3%
PII detection recall on a financial-services chatbot moderation pipeline.
Solutions
One partner. Every capability your model needs.
Eight capabilities. Proven execution. Beating industry benchmarks every time.
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Customer story
140K+ training assets across 28 countries and 38 languages
For one of the leading smartphone manufacturers in the world, we delivered 140K+ assets across a diverse range of data — collected, annotated, and tested to train eyes, hands, and voice.
140K+
assets / 24 weeks
WHO WE SERVE
Built for the teams shipping AI
From frontier labs to regulated banks, with eight customer types and live programs in each.
AI Labs
AI labs and foundational models
Our offerings span pre-training corpora, including expert SFT/CoT and RLHF preference data, and red-teaming for frontier labs building foundation models.
Technology
Technology
We provide personal-computing, search, social, and devices, with multi-program GenAI workflows at hyperscale across eyes, hands, and voice.
Robotics
Robotics
We deliver ego-exo capture, teleoperation, manipulation trajectories, sim-to-real support, long-horizon task episodes.
Healthcare
Healthcare
We run clinician-graded data, safety-critical evaluation, and bias audits mapped to HIPAA, FDA AI/ML SaMD, and EU AI Act.
CUSTOMER STORY
50,000 hours that taught a robot to grip
Robotics Studio VLA program
50,000 hours of usable egocentric data for a Visual-Language-Action model
We built a high-diversity, task-specific dataset of household dexterous manipulation, and executed collection across moderated and unmoderated settings. We validated the prototype device performance and created a reusable data pipeline extensible to new tasks, devices, and product categories.
Gen AI lifecycle
Catch the harness, context, and model drift before your users do
Shipping is just the start of your GenAI journey. We partner with you throughout the GenAI lifecycle to deliver outcomes that the business cares about.
Corpus build at frontier scale across text, audio, image, video, code, and sensor.
- Ego-exo video collection
- Teleoperation demonstrations
- UMI data capture
- Sensor fusion datasets
Expert demonstrations from 200+ domain scientists, PhDs, MDs, engineers.
- Domain demonstrations
- Manipulation trajectories
- Imitation learning data
- Language-conditioned actions
Human preference data for RLHF, safety alignment, regression sets.
- HITL preference feedback
- RLHF-style robotics data
- Failure & edge-case harvesting
- Regression test suites
Continuous data engine that catches model drift before your users do.
- Continuous data engine
- Live edge-case pipeline
- Adversarial red-teaming
- Retraining trigger detection
Agentic AI Studio
Firstsource’s Agentic AI Studio
Explore the world of task models, assess their performance, integrate diverse models to craft Agentic AI workflows.
Xplore
Discover high-impact workflow and program design across modalities, domains, and skill profiles.
Evaluate
Validate with multi-pass evaluation, IAA scoring, Elo calibration, and outlier-judge flagging built in.
Weave
Orchestrate annotation with speeds 6× faster than marketplace and 50× faster than open-source for video.
Monitor
Track performance with dashboards covering 35+ KPIs across category, experiment, and model.
Proof of delivery
What we’ve delivered for our operators
Eval · Frontier AI Lab
100+
vetted STEM evaluators
Arena-style head-to-head ranking across 22 STEM capabilities, including physics, chemistry, biology, math, CS, and robotics. Elo calibration and outlier-judge flagging built into the pipeline.
Program · Hyperscaler
0%
Error rate | 3-week turnaround
20,000+ prompts and responses delivered across 5 content categories and 7 coding languages. 100+ SMEs deployed.
Perception · Auto OEM
>99%
Accuracy | occluded-object tracking
10,000 dashcam clips annotated across 50+ object categories, including occluded and obstructed object tracking, accelerating go-to-market in new geographies.
WHY FIRSTSOURCE WINS
What teams try. What actually works.
The shortcuts AI teams reach for first, and why each one stops scaling.
WHAT TEAMS TRY
WHY IT FAILS
WHAT CHANGES WITH FIRSTSOURCE
Scrape public web at scale
Copyright exposure, eval contamination, no rare-domain coverage, no expert grading.
Proprietary first-party capture, expert-graded by PhDs, MDs, and engineers across moderated, field, and crowd collection.
Anonymous click-worker marketplaces
No domain depth. STEM, clinical, legal, code all degrade. Quality drift inside the first month.
Large expert pool with vetted credentials, 100's of domain scientists, ISO-aligned QC discipline.
Recycle last cycle’s training data
Drifts from current user behavior, language, and regulation. The edge cases the model needs to learn don’t appear in the corpus.
Continuous data engine: fresh capture, regression sets, and drift detection tied to live model performance.
Build the data team in-house
12–18 months to staff. Multilingual coverage is unreachable. Ops overhead crowds out research.
Sub-48-hour program activation across 100+ countries via the Gigsourcing Platform.
Single-modality annotation vendor
One pipeline for text, another for audio, another for video. RLHF and red-teaming go elsewhere.
Eight named capabilities under one operating model: eval, SFT/CoT, annotation, RLHF, red-teaming, safety, physical AI, and OTS.
Synthetic data only
Distribution collapse. Edge cases never appear. Safety and refusal calibration cannot be synthesized.
Human-graded preference data, adversarial corpora, and real-world capture, alongside any synthetic generation.
TRUST & COMPLIANCE
EU AI Act Article 10 doesn’t wait. Neither does our compliance team.
We operate inside the regulatory frameworks that matter to AI customers, by design, not by exception.
Regulatory framework
EU AI Act · Article 10
HIPAA §1557
FDA AI/ML SaMD guidance
CFPB · model risk
GDPR · UK GDPR
PII multi-jurisdiction
Certifications
SOC 2 Type II
CFPB 12 CFR 1024.41
ISO 27001
CFPB 12 CFR 1024.41
ISO 17100 (multilingual)
CFPB 12 CFR 1024.41
HIPAA-aligned
CFPB 12 CFR 1024.41
PCI-DSS
CFPB 12 CFR 1024.41
Cert years to be confirmed by Firstsource compliance team before publish.
INSIGHTS
Latest from the Firstsource team
Insights from the field, real operations, real outcomes, and perspectives from the people making it work in live operations.
Case Study
Penetration testing using GenAI enhances platform safety and trust for an online marketplace for short and long-term homestays and experiences
Discover how a global marketplace for homestays and experiences partnered with Firstsource to proactively secure its platform against identity and listing fraud through GenAI-powered penetration testing, bolstering user trust and safety.
Case Study
Delivering 1 million AI tasks in 5 weeks: Firstsource enhances GenAI model with 98% accuracy
Goal: A leading tech company partnered with Firstsource to enhance their virtual assistant's GenAI model using Reinforcement Learning from Human Feedback (RLHF). The goal was to improve accuracy and reliability by training the model with high-quality, annotated data, creating and verifying multi-turn conversations across multiple domains within a tight deadline. How we made it happen:Our tailored approach ensured precise execution at scale. Here's how:
Case Study
Rapid improvement in GenAI models using high quality, multilingual STEM content, with 100% quality compliance for a global tech giant
Firstsource delivered 120K+ high‑quality STEM content items in 10 languages for a GenAI model, achieving full compliance and rapid onboarding of expert creators.
Contact us
Collect it. Manage it. Train your models on it.
Tell us what you’re building. A program lead replies inside one business day.
- Talk to a real program lead
- Sample dataset returned in 5–10 business days
- Compliance docs (SOC 2, ISO, HIPAA-aligned) on request
- NDA before any data exchange