Fastino
Fastino is a Palo Alto-based applied AI lab building small encoder-based language models (the GLiNER family and TLMs) for production text extraction, classification, safety moderation, and PII detection, monetized through the Pioneer fine-tuning and inference API.
- Company typePrivate
- Founded2024
- HeadquartersPalo Alto, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
What Fastino does
Fastino (also operating as Fastino Labs and Fastino AI; legal entity Fastino Inc.) is a Palo Alto-based applied AI research lab founded in 2024 that builds small, encoder-based bidirectional transformer language models — branded as Task-Specific Language Models (TLMs) and the GLiNER family — for production AI workloads including entity extraction, text classification, structured data parsing, LLM safety moderation, and multilingual PII detection. The company's core technical bet is that tasks typically handled by large autoregressive LLMs can be reframed as schema-conditioned text classification, enabling models 23-90x smaller than frontier competitors to match or exceed their accuracy at a fraction of the inference cost and latency (sub-100ms). Fastino's products are released as open-source model weights under Apache 2.0 on Hugging Face and GitHub — generating 3,000,000+ monthly downloads, 3,200+ GitHub stars, and 1.1B+ end users reached through customer integrations.
Fastino monetizes through Pioneer, an agentic platform launched in April 2026 that automatically fine-tunes open-source base models (Qwen, Gemma, Llama, Nemotron, GLiNER) from a single prompt and continuously retrains deployed models on live production data via adaptive inference, with end-to-end runs priced at approximately $35 each. The commercial surface is the Pioneer inference API (usage-based, self-serve) supplemented by an enterprise field-sales motion for production deployments. Revenue is not publicly disclosed; total funding raised is approximately $25M across a $7M pre-seed (Nov 2024, Insight Partners and M12), a $17.5M seed (May 2025, Khosla Ventures), and an undisclosed allocation from Dropbox Ventures (Jul 2025), with NEA and Valor Equity Partners also listed as investors. The customer base is horizontal — spanning enterprise AI teams, AI agent developers, safety and compliance teams, and privacy/data governance teams — and is accessed through a developer-led GTM anchored on open-source distribution, an active community (Discord, Reddit r/GLiNER, YouTube, arXiv publications), and Hugging Face/GitHub as primary discovery channels.
Fastino firmographics
Firmographics- Name
- Fastino
- Legal name
- Fastino Inc.
- Website
- https://fastino.ai
- Company type
- Private
- Founded year
- 2024
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Short description
- Fastino is a Palo Alto-based applied AI lab building small encoder-based language models (the GLiNER family and TLMs) for production text extraction, classification, safety moderation, and PII detection, monetized through the Pioneer fine-tuning and inference API.
- Ownership category
- akta.pro rank
Fastino industry classification
Industry- Product category
- Natural Language Processing Software
- NAICS
- Computer Systems Design Services (541512), Computer Systems Design and Related Services (5415)
- SIC
- Services-Prepackaged Software (7372), Services-Computer Programming Services (7371)
- akta.pro primary industry
- NLP Developer Tools & Evaluation (prompting, testing, benchmarks) (HDAAADAK)
- akta.pro secondary industry
- Synthetic Data & Data Augmentation for Foundation Models (HDAAACAK)
Keywords
Where Fastino is headquartered
LocationHeadquarters
- HQ city
- Palo Alto
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
Fastino business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Technology or R&D
Revenue model
- Pioneer Inference API: Pioneer is described as an inference API built by Fastino Labs, monetizing production deployment of Fastino's models and fine-tuned variants for developers and enterprises. Pricing is referenced via a /pricing page but specific tiers were not disclosed in the source material.
- Pioneer Fine-tuning Service: Pioneer provides managed fine-tuning of open-source small language models, with end-to-end runs reported at approximately $35 each and completing in around 6 hours, representing a per-job managed service revenue stream.
- Open-source model distribution: GLiNER, GLiNER2, GLiGuard, and GLiNER2-PII are released under Apache 2.0 license and distributed on Hugging Face and GitHub; while the model weights are free, this drives adoption that funnels into the paid Pioneer API.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Usage-based | Pay-as-you-go | Pioneer fine-tuning runs at approximately $35 per end-to-end run (around 6 hours each) |
| Usage-based | Pay-as-you-go | Pioneer inference API pricing is referenced via a /pricing page but not publicly detailed in the source material |
| Other | Pay-as-you-go | Open-source models available free under Apache 2.0 license |
Go-to-market motion4 records
Distribution channels4 records
Marketing channels11 records
Fastino product offering
Product offeringCore offering
Fastino builds small, encoder-based bidirectional transformer language models (Task-Specific Language Models) and packages them with Pioneer, an agentic fine-tuning and adaptive inference platform. The offering includes the GLiNER family of open-source models (GLiNER, GLiNER-2, GLiGuard, GLiNER2-PII) for named entity recognition, classification, safety moderation, and PII detection, delivered via open-source weights, managed inference API, or on-prem deployment.
Product overview
Fastino Labs is an applied AI research lab operating a platform-plus-modules architecture centered on small, task-specific language models. The core platform is Pioneer, a fine-tuning and inference agent that automatically retrains open-source small language models (Qwen, Gemma, Llama, Nemotron, and GLiNER) on live production data. Surrounding it are the GLiNER family of open-source models: GLiNER for generalist named entity recognition, GLiNER-2 for schema-conditioned multi-task information extraction and classification, GLiGuard for LLM safety moderation, and GLiNER2-PII for multilingual PII detection and redaction. All open-source models are released under Apache 2.0 and can be self-hosted on-prem/air-gapped or deployed via Pioneer's inference API.
Differentiator
Problem solved
Functional benefit
Brands
- Pioneer: An AI platform/agent for fine-tuning and inference of open-source small language models, with adaptive inference that continuously retrains deployed models on live production data. Operated at pioneer.ai.
- GLiNER
Products and services
- Pioneer An AI agent platform from Fastino Labs that enables developers to fine-tune and deploy open-source small language models (Qwen, Gemma, Llama, Nemotron, GLiNER) with a single prompt. It features adaptive inference that continuously retrains deployed models on live production data to improve accuracy over time, exposing a managed inference API for production deployment.
- GLiNER-2 An open-vocabulary, schema-conditioned multi-task information extraction and classification model used across production systems serving 1B+ daily end users, providing entity extraction, text classification, and structured JSON parsing at sub-100ms average latency. Released under Apache 2.0.
- GLiGuard A 300M parameter encoder-based safety moderation model that evaluates prompt safety, response safety, harm categorization, and jailbreak detection in a single forward pass with sub-30ms latency, matching or exceeding the accuracy of guard models 23-90x its size. Released under Apache 2.0.
- GLiNER2-PII A 300M parameter multilingual model for detecting and redacting personally identifiable information across 42 customizable entity types with deterministic one-pass inference across seven languages, designed for production privacy workflows. Released under Apache 2.0.
- GLiNER The generalist open-source model for named entity recognition using a bidirectional transformer; the foundational model of the GLiNER family that powers Fastino's text extraction offerings. Released under Apache 2.0.
Quantifiable outcome
- GLiNER-family models are referenced as 1000x faster than frontier LLMs for certain inference tasks
- +6 more outcomes
Companies that use Fastino
Customer profileSegments4 records
Ideal customer profiles4 records
Fastino technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
AI capability6 records
Feature6 records
Fastino partnerships and signals
Strategic signalPartnerships
One partnership is on record.
- Hugging FacecoreFastino distributes its open-source models (GLiNER2, GLiGuard, GLiNER2-PII) on Hugging Face under Apache 2.0. Hugging Face serves as the primary distribution and discovery channel for Fastino's models, contributing to the reported 3,000,000+ monthly downloads.
Scale indicators12 records
Recent moves6 records
Expansion highlights6 records
Fastino competitors and assessment
Company assessmentBroad incumbents
- Hugging Face: The dominant open-source model hub and inference platform on which Fastino distributes GLiNER-family models. Hugging Face is both a critical distribution partner and a competitor for hosted inference and enterprise deployment of open-source language models.
- Cohere: Enterprise-focused NLP platform offering classification, extraction, and generation models via API and private deployment. Competes with Fastino on enterprise NLP workloads and on-prem/air-gapped deployment for regulated buyers.
- Scale AI: Provides data infrastructure, evaluation, and applied AI products for enterprise and government, including content moderation and safety — overlapping with Fastino's GLiGuard and PII detection use cases.
- Anyscale: AI compute platform (Ray-based) used to serve and fine-tune open-source LLMs at scale. Competes indirectly with Pioneer for the 'production-scale open-source model serving' buyer.
- Anthropic: Frontier LLM provider whose Claude models compete with GLiNER-family models for classification, extraction and safety workloads; Claude Haiku in particular targets the low-latency/cost tier where Fastino positions its TLMs.
- OpenAI: Frontier model provider whose GPT-4o/4o-mini and Privacy Features are direct benchmarks for Fastino's efficiency claims (2x price efficiency vs GPT-4o) and PII detection capabilities (GLiNER2-PII vs OpenAI Privacy Filter).
Direct peers
- Together AI: Provides hosted inference and fine-tuning for open-source large language models targeting developers and enterprises. Closely comparable to Fastino's Pioneer platform on the inference-API and managed-fine-tuning GTM, though Together focuses on larger open-source models.
- Replicate: A cloud platform for running and fine-tuning open-source ML models via an API. Like Fastino, Replicate targets developers who want to deploy models without managing GPU infrastructure, making it a direct competitor for the same PLG developer audience.
- Modal Labs: Serverless infrastructure for running AI/ML workloads including fine-tuning and inference of open-source models. Competes with Fastino for developer mindshare on the 'deploy open-source models without managing GPUs' axis.
- Mistral AI: Open-weight foundation model provider shipping efficient small and mid-sized LLMs with both open releases and a managed API. Overlaps with Fastino on task-optimized small language models and on the open-weights-plus-API monetization model.
Market position
Strengths4 records
Weaknesses4 records
Competitive moat6 records
Key risks6 records
Key highlights6 records
Customer concentration
Fastino social profiles
Digital presenceFastino financial estimates
Financial estimateRevenue estimate
Valuation estimate
Fastino leadership team
Management profileNumber of profiles
Profiles2 records
Fastino funding detail
Funding detailFunding overview
Funding rounds3 records
Investors7 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Fastino M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Fastino
What does Fastino do?
Fastino builds small, encoder-based bidirectional transformer language models (Task-Specific Language Models) and packages them with Pioneer, an agentic fine-tuning and adaptive inference platform. The offering includes the GLiNER family of open-source models (GLiNER, GLiNER-2, GLiGuard, GLiNER2-PII) for named entity recognition, classification, safety moderation, and PII detection, delivered via open-source weights, managed inference API, or on-prem deployment.
Is Fastino a public or private company?
Fastino is a private company. It is classified as venture growth investor backed and is currently operating.
When was Fastino founded?
Fastino was founded in 2024. It employs 11 to 50 people.
Where is Fastino based?
Fastino is headquartered in Palo Alto, United States, in the North America region.
How does Fastino make money?
Three revenue lines are on record. Pioneer Inference API is the primary driver. The others are pioneer Fine-tuning Service and open-source model distribution.
Who are Fastino's main competitors?
Broad incumbents on record are Hugging Face, Cohere, Scale AI, Anyscale, Anthropic and OpenAI. Direct peers are Together AI, Replicate, Modal Labs and Mistral AI.
Does Fastino have an API?
Yes. Fastino Inc. develops specialized AI models and provides APIs designed to support structured data extraction, classification, reasoning, and production AI workflows. The Pioneer platform exposes an inference API for fine-tuned open-source small language models (Qwen, Gemma, Llama, Nemotron, GLiNER), and the GLiNER/GLiGuard/GLiNER2-PII models are also publicly hosted on Hugging Face under Apache 2.0 for integration. Developer documentation is at docs.pioneer.ai/introduction.
What industry is Fastino in?
Fastino's product category is Natural Language Processing Software. Its primary akta.pro industry code is HDAAADAK, NLP Developer Tools & Evaluation (prompting, testing, benchmarks), with a secondary code of HDAAACAK, Synthetic Data & Data Augmentation for Foundation Models. Its NAICS code is 541512 and its SIC code is 7372.