LinkedIn · Aug 2026
Recent company post about Nanonets’ open-source coding-agent context layer, indicating expansion beyond document automation.
Company research
Public company, workplace, funding, and market signals
Updated Aug 16, 2026
Overview
Nanonets is an AI agent / workflow automation company focused on automating document- and data-heavy business processes (especially finance/AP, claims, order management) and delivering structured data into enterprise systems like SAP and Salesforce.
Primary product
AI agents / document workflow automation platform (including OCR and unstructured data extraction)
Founded
2017
Headquarters
San Francisco, California, United States
Team size
100-150 employees
Industry
Software Development
Sub-industry
AI workflow automation / intelligent document processing / AI agents
Offices
Mumbai, Maharashtra, India
Santa Clara, California, United States
San Francisco, California, United States
Business model
B2B SaaS
usage-based / page-volume pricing
enterprise sales
Funding
Stage
Series B
Total raised
$40.5M
Latest round
Series B · Mar 2024
Latest amount
$29M
Mar 2024 · Accel India
Feb 2022 · Elevation Capital
Apr 2017
People & investors
Leadership
CEO
Founder
Lead, People Success
Growth Strategy Manager
Head of Finance
Engineering Manager Developer
Product Generalist
Work & culture
Public signals suggest a product- and engineering-heavy team focused on automation, AI/ML quality, and shipping enterprise workflows; the company also appears to hire across India and the US. No explicit benefits page evidence was found in the searched sources.
Compensation
No public compensation bands were found in the searched sources. Job postings were available, but no salary data was surfaced in primary sources.
Product & market
Pricing
Publicly visible pricing signals include a free trial/demo and page-based plans, including 500 pages free and 10,000 pages/month for $999 on a public pricing surface. Enterprise pricing likely varies by volume and use case.
Differentiators
- —Focus on autonomous AI agents for end-to-end workflow execution, not just extraction
- —Strong emphasis on structured output into systems of record like SAP/Salesforce
- —Document/OCR products tuned for real-world enterprise documents and edge cases
- —Public claims of high accuracy on finance, legal, and healthcare benchmarks
- —No-code / low-code workflow automation positioning
Technology
AWS
Python
Node.js
JavaScript
TypeScript
React
Django
Docker
Kubernetes
PostgreSQL
MySQL
MongoDB
Redis
Prometheus
Grafana
Datadog
ELK
TensorFlow
PyTorch
Keras
Customers
P&G
Bayer
Roche
Schneider Electric
Mondelez
Asian Paints
Competitors
ABBYY
Hyperscience
Rossum
Docparser
Google Document AI
AWS Textract
Azure Form Recognizer
LandingAI
Reducto
Extend
Scale & contact
Estimated revenue
$1M-$10M (Exa estimate; also surfaced as USD 4.2M annual revenue in Exa profile)
Estimated monthly visits
283.2K
Traffic estimate as of Jun 2026
Latest news
LinkedIn · Apr 2026
Recent company post claiming OCR-3 benchmark leadership and describing product capabilities including bounding boxes, confidence scores, integrated OCR, and native VQA.
Nanonets Research · Apr 2026
Launch of OCR-3, described as a Mixture-of-Experts document model with /parse, /extract, /split, /chunk, and /vqa endpoints for structured document processing.
Nanonets Blog · Mar 2026
Benchmark roundup comparing AI models on document tasks; Nanonets highlighted OCR2+ performance and cost positioning.
Nanonets Health · Apr 2025
Announces a healthcare revenue-cycle partnership with Healthie to automate intake, verification, pre-authorization, scheduling, claims, and follow-up workflows.
Jobs and careers at NanoNets
0 jobs at NanoNets
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