Instant Context

Tone Matching

Continous Adaptation

All Use Cases

Your agent understands what your users mean — instantly.

Book my usual cafe for tomorrow’s meeting.

Got it. booking Café Luna for 10 AM. Same window seat as last time?

Searching for answers…

Ask a question…

Sign in with Google

Instant Context

Tone Matching

Continous Adaptation

All Use Cases

Your agent understands what your users mean — instantly.

Book my usual cafe for tomorrow’s meeting.

Got it. booking Café Luna for 10 AM. Same window seat as last time?

Searching for answers…

Ask a question…

Sign in with Google

PERSONALIZATION

Pioneer API (Beta)

Relationship memory, outcome prediction, personalized retrival

PERSONALIZATION

Pioneer API (Beta)

Relationship memory, outcome prediction, personalized retrival

PERSONALIZATION

Pioneer API (Beta)

Relationship memory, outcome prediction, personalized retrival

SMALL AGENT MODELS

GLiNER-2 XL for Agents

Model guardrails, text classification, retrieval with <100ms latency

SMALL AGENT MODELS

GLiNER-2 XL for Agents

Model guardrails, text classification, retrieval with <100ms latency

SMALL AGENT MODELS

GLiNER-2 XL for Agents

Model guardrails, text classification, retrieval with <100ms latency

Personalize your agent with Pioneer

Instant User Context

We build a world model of a new user in minutes, using publicly available data and insights pooled from similar user embeddings.

Tone Matching

Agents replicate the user’s unique tone of voice, phrasing style, and communication rhythm when generating text.

Continous Adaptation

The Learning from Corrections and Outcomes pattern enables your AI agents to improve automatically from user feedback.

Our Research

GLiNER: Generalist and Lightweight Model for Named Entity Recognition
Adaptive Personalization via Predictive Processing and Bayesian Inference
GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface
Beyond Reactivity: Measuring Proactive Problem Solving in LLM Agents (PROBE benchmark)
GLiNER: Generalist and Lightweight Model for Named Entity Recognition
Adaptive Personalization via Predictive Processing and Bayesian Inference
GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface
GLiNER: Generalist and Lightweight Model for Named Entity Recognition
Adaptive Personalization via Predictive Processing and Bayesian Inference

Our Team

We believe the next breakthroughs in intelligence research will come from billions of agentic employees, and we are in a unique position to help them. If you have aligned expertise and are excited by our mission, please get in touch.


Founding Team

Ash Lewis @ash_csx

George Hurn-Maloney @george_onx

Tom Lewis

Julia White

Urchade Zaratiana @urchadeDS

Varun Bharadhwaj

Dheeraj Rajagopal @dheerajgopal

Henrijs Princis

Gil Pasternak

Kelton Zhang

Matt Thomas

Dhruv Atreja @DhruvAtreja1


Community & support

Join the community

Join our active community on Discord.

Join the community

Join our active community on Discord.

Join the community

Join our active community on Discord.

Need help?

Get in touch with our support team.

Need help?

Get in touch with our support team.

Need help?

Get in touch with our support team.