Startup profile · funding coverage
Labelbox funding, valuation and investors
Training data platform for ML teams — labeling, curation, and model evaluation.
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Funding, valuation & investors
Answer-first snapshotLatest funding
Series C
$40M · February 2021
Latest known valuation
Not publicly disclosed
Total disclosed equity funding
$65M
Excludes debt, grants, acquisitions, secondaries, and IPO proceeds.
Current status
private
growth · San Francisco, California
Investors in latest funding
Lead: B Capital Group
Other: Andreessen Horowitz , First Round Capital , Kleiner Perkins
Overview
Labelbox provides a training-data platform where ML teams label, curate, and manage datasets for supervised learning, computer vision, and LLM fine-tuning. The company raised a $25M Series B in February 2020 led by Andreessen Horowitz and a $40M Series C in February 2021 led by B Capital Group, with First Round and Kleiner Perkins participating.
Why Labelbox is interesting
Labelbox sits under every supervised ML stack — data quality remains the bottleneck even in the LLM era where human feedback loops matter as much as pre-training data.
Product & use cases
Labelbox combines data labeling workflows, quality management, model-assisted labeling, and evaluation tools — supporting image, text, video, and LLM RLHF annotation at scale.
- Computer vision dataset labeling for autonomous systems
- LLM fine-tuning and RLHF human feedback collection
- Model evaluation and error analysis on labeled datasets
- Active learning pipelines to prioritize labeling spend
Key facts
- Series C (Feb 2021): $40M led by B Capital — Labelbox press
- Series B (Feb 2020): $25M led by a16z — Labelbox press
- Training data platform for ML and LLM fine-tuning
Funding history (newest first)
Investors in our directory
Funds linked from Labelbox's profile — open a fund page for stage focus and related deal articles.
Competitive landscape
Edge: Enterprise-grade labeling ops with model-assisted acceleration — reduces cost per label vs. pure manual annotation.
Data labeling commoditized at the low end but remains critical for high-quality ML. Labelbox competes with Scale AI's scale and vertical integration. LLM era shifted demand toward RLHF and evaluation, not just image boxes.
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Scale AI direct
Dominant data labeling vendor with government and enterprise contracts.
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Snorkel AI adjacent
Programmatic labeling vs. human annotation focus.
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SuperAnnotate direct
Computer vision labeling platform.
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Hive / Appen adjacent
Crowd labeling services.
Notable stories
- Labelbox raised Series B and C in consecutive Februarys (2020, 2021) — riding the computer vision labeling wave before pivoting tooling toward LLM RLHF.
Industries
FAQs about Labelbox
Practical answers founders, operators, and investors typically search for.
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