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Tilde Research

Full-stack AI interpretability and control solutions

Overview

Tilde Research builds full-stack interpretability solutions for AI and machine learning, including interpreter models and control technology to optimize how elicited features are orchestrated in inference pipelines with human guidance. It combines general interpreter models with control mechanisms to steer feature flow during inference and integrate with existing AI stacks for human-in-the-loop evaluation and post-training adjustments. Unlike approaches that focus only on explanations, it emphasizes deployment-time control and orchestration to keep AI aligned with human expertise. Its goal is to help organizations deploy AI that can handle complex tasks safely and with clearer alignment to human input.

Significant Headcount Growth

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About Tilde Research

Simplify's Rating
Why Tilde Research is rated
C
Rated C on Competitive Edge
Rated C on Growth Potential
Rated C on Differentiation

Industries

Data & AnalyticsConsultingEnterprise SoftwareAI & Machine Learning

Company Size

1-10

Company Stage

N/A

Total Funding

N/A

Headquarters

Palo Alto, CA

Founded

2024

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Simplify's take

What believers are saying

  • Tilde launched One Layer Deeper on March 8, 2026, signaling active community building.
  • Recent posts on Parallax and Wall Attention show continued technical output through June 2026.
  • Open roles for ML Research, ML Engineering, and infrastructure indicate ongoing hiring in San Francisco.

What critics are saying

  • Tilde Research has no disclosed revenue, making the 2026 business model unproven.
  • Open-source interpretability commoditizes quickly; Anthropic and OpenAI can copy methods by 2027.
  • If One Layer Deeper fails to produce deployable control, Tilde becomes a research blog.

What makes Tilde Research unique

  • Tilde Research sells mechanistic interpretability as a control product, not a paper shop.
  • Its July 2025 seed round with Khosla Ventures funded a dedicated Bay Area lab.
  • The blog shows integrated research on architecture, objectives, and optimizers, not narrow tooling.

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