Pieces - Long term memory for your whole workstream

What is Pieces

Every developer knows that feeling—the context switch between Slack and your IDE, the bookmark folder that grew unmanageable, the half-remembered solution from last week's debugging session. You're not just writing code; you're managing an overwhelming amount of information across dozens of tools. And somewhere in that noise, your best ideas and critical context get lost.

That's exactly the problem Pieces was built to solve.

Pieces is the first OS-level, local-first long-term memory engine designed specifically for developers. Think of it as your workstream's memory—not just a clipboard manager or a code snippet tool, but an intelligent system that actively remembers everything you've done, seen, and learned across your entire workflow. It integrates seamlessly with the tools you already use, working quietly in the background to capture, organize, and retrieve the context that matters to you.

What makes Pieces different from traditional AI assistants is its memory architecture. While most AI tools rely on Large Language Models that know things from their training data, Pieces knows you—your specific projects, your coding patterns, your team's conventions, and the solutions you've discovered along the way. It combines the power of on-device AI with privacy-first design, ensuring your sensitive work context never leaves your machine unless you explicitly choose to share it.

The result? You stay in flow longer. You find that snippet you saved three weeks ago without digging through folders. You pick up right where you left off after a meeting. You focus on creative problem-solving instead of information management.

And developers have noticed. More than 150,000 high-performing developers at companies like Google, Amazon, Microsoft, Meta, Shopify, and Notion now use Pieces as an essential part of their daily workflow. They're the teams building the products you use—and Pieces helps them do it faster, smarter, and with less friction.

---

Core Features of Pieces

Pieces isn't just a single tool—it's a comprehensive memory ecosystem that transforms how you work. Let me walk you through the capabilities that make this possible.

Long-Term Memory System

At the heart of Pieces is the LTM-2 engine—a proprietary long-term memory system that operates at the OS level. Unlike temporary context windows in traditional AI, LTM-2 actively forms and maintains memories of your work over time. It uses technology inspired by REM sleep cycles to create meaningful associations between related pieces of information, so when you search for something, you find not just exact matches but contextually relevant results. Remarkably efficient, it can store 18 months of structured memory in just 4GB of storage.

AI Copilot That Actually Knows You

Your AI assistant should understand what you already know—and that's exactly what Pieces Copilot does. Rather than relying solely on public LLM knowledge, it provides context-aware help based on your personal workstream. It knows your codebase, your preferences, and your past solutions. So when you ask a question, you get answers that account for what you've already discovered, not just what exists in generic training data. This personalized approach delivers a 380% improvement in recall accuracy.

Pieces Drive: Workflow Storage with AI Enhancement

Save anything from code snippets to entire workflows, and Pieces automatically enriches them. It detects sensitive information, adds relevant context, and transforms raw snippets into searchable, reusable assets. For teams, Pieces Drive becomes a shared knowledge base where everyone contributes to a growing library of solutions—without the mess of scattered Slack messages and forgotten documents.

Multi-LLM Flexibility

You deserve the freedom to choose the right model for the task. Pieces supports OpenAI, Anthropic (including Claude 4 Sonnet and Opus), Google Gemini 2.5, Ollama, and more. Switch between models depending on your needs—whether you prioritize speed, reasoning capability, or specific domain expertise. You're not locked into any single provider.

MCP Integration

Through Model Context Protocol (MCP), Pieces connects directly with tools like GitHub Copilot, Claude Desktop, Cursor, and Goose. This means you can access your long-term memory directly from the AI tools you already use, eliminating context-switching while leveraging the power of Pieces behind the scenes.

Cross-Platform Plugins

Whether you prefer Chrome for research, VS Code for development, or work across Windows, Linux, and macOS, Pieces fits into your existing setup. Plugins for major platforms and browsers let you capture context without interrupting your flow—work where you normally work, let Pieces handle the memory.

---

Who Uses Pieces

Pieces adapts to how you work. Whether you're diving deep into code, running meetings, or collaborating across teams, here's how different types of developers get value from Pieces.

Researchers and Technical Writers

If you've ever felt overwhelmed by hundreds of bookmarks, open tabs, and scattered notes from weeks of investigation, Pieces changes that entirely. It automatically captures every link you visit, highlight you make, and keyword you search for—building a searchable memory of your research journey. You never need another bookmark folder. Just ask Pieces what you were looking at last month, and you'll find it instantly.

Meeting Participants

How many great ideas shared in meetings get lost in the noise? Pieces silently captures the content shared during calls, the links mentioned, and the context of discussions. After the meeting, you have a complete record—not just notes, but the full context. Share specific insights with teammates later without trying to remember what was said or where that link was posted.

Deep Workers

When you're in the zone—debugging a tricky issue, writing a complex feature, or architecting a solution—the last thing you want is to break your flow to search for something you saw hours ago. Pieces preserves your mental state, letting you resume exactly where you left off, even after switching contexts. It handles the information management so you can focus on the creative work that requires your full attention.

Collaborating Teams

Knowledge silos kill team velocity. When one developer solves a problem that another faced last week, everyone loses time re-solving the same challenges. Pieces captures context across tools and team members, building a shared knowledge base that grows smarter over time. New team members onboard faster. Decisions get made with full context. The team's collective memory becomes a real, searchable asset.

---

Technical Features

If you're curious about what makes Pieces work under the hood, this section is for you. The technical architecture reflects one core principle: privacy shouldn't mean sacrificing capability.

LTM-2: The Memory Engine

The Long-Term Memory 2 engine is Pieces' proprietary technology for active memory formation and retrieval. Unlike passive storage systems, LTM-2 continuously learns from your workflow patterns through its Workstream Pattern Engine, identifying relationships between your activities and forming memories that matter. The architecture supports both structured data (code, documents) and unstructured context (conversations, links), creating a comprehensive picture of your work over time.

On-Device Machine Learning

All intelligence runs locally on your machine. Pieces uses a combination of algorithms including TF-IDF for semantic search, Support Vector Machines (SVMs) for classification, Long Short-Term Memory networks (LSTMs) and Recurrent Neural Networks (RNNs) for sequence learning. These models run with hardware acceleration, meaning you get powerful AI capabilities without the cloud compute costs or latency. Critically, these on-device "nanomodels" are trained only on synthetic data—never on your actual content, ensuring privacy at every level.

Performance That Scales

The numbers speak for themselves: 380% improvement in recall accuracy over traditional approaches, and CPU and RAM usage that's 14 times more efficient than cloud-based alternatives. That efficiency means Pieces runs quietly in the background without draining your system resources. You get enterprise-grade AI capability on a laptop.

Privacy Architecture

Pieces follows a strict local-first philosophy. By default, your data never leaves your device. Cloud sync is entirely optional—enabled only when you explicitly choose it. Perhaps most importantly, your data is never used to train any models, whether Pieces' internal systems or third-party LLM providers. You're in complete control: enable, disable, or delete any memory at any time.

Security You Can Trust

For teams and enterprises, Pieces operates on SOC 2 compliant infrastructure with continuous security audits. Authentication uses Auth0 with full MFA (multi-factor authentication) support, giving security teams the controls they require. Whether you're an individual developer or managing a team, your sensitive work context stays protected.

---

Pricing Plans

Pieces offers three tiers designed for different needs—from individual developers exploring the product to high-performance teams requiring shared knowledge and advanced capabilities.

Which version should you choose?

If you're a solo developer building personal projects or exploring AI-assisted coding, the Free version gives you substantial capability without any cost. You get local memory, Copilot assistance, and nine months of personal context—more than enough to transform how you work.

If you're a professional developer who needs the latest and most capable AI models, Pro at $18.99/month unlocks Claude 4 Sonnet and Opus, Gemini 2.5, and early access to new model releases as they become available.

If you're leading or working in a team where knowledge sharing matters, Teams gives you shared context windows, collaborative storage, and the ability to choose which LLM your team uses. Contact Pieces directly for custom pricing based on your team size and requirements.

---

Frequently Asked Questions