Persistent Agent Memory That Never Bloats Your Context

What is the "Zero Data Hostage" Guarantee?

Across every tier (Community, Pro, and Team), your memories are stored in an open, unencrypted SQLite database directly on your own disk at ~/.titan/mem/memory_graph.db. We believe your engineering knowledge belongs exclusively to you. If you ever cancel a subscription or uninstall Titan Mem, your database stays on your machine. You can query, inspect, backup, or export your data anytime using standard tools (sqlite3, Python, DBeaver) with zero vendor lock-in.

Can I use Titan Mem on both my laptop and desktop?

Yes. The free Community edition can be installed on any single machine. For developers who switch between a workstation, laptop, and cloud dev container, a single Pro Developer license activates up to 3 personal devices under one key via hardware node-locking. Our automated zero-knowledge encrypted background sync relay is currently in private preview for Pro users—in the meantime, each activated machine benefits from full local sub-3ms routing and cross-session persistence.

Does storing session context make the model generate tokens faster?

No—and anyone claiming local memory accelerates cloud LLM generation speed is being dishonest. Model inference speed is physically constrained by cloud GPU cluster latency and Time-To-First-Token (TTFT). What Titan Mem eliminates is human wall-clock debugging hours and runaway token costs. Instead of pasting 20,000-token historical transcripts or having a new engineer spend 4 hours re-solving an obscure allocator bug, Titan Mem injects a <150 token distilled rule on prompt 1.

How does Titan Mem prevent hallucinations and bug regressions?

Verified outcomes over raw transcripts. Dumping raw chat logs into an agent pollutes the context with terminal noise. The proprietary Titan Mem Engine™ extracts verified debugging patterns and links historical decisions to preceding fixes. When a compiler or test fails, the agent is automatically anchored to your project's verified history rather than exploratory hallucination.

How does Titan Mem handle hundreds of enterprise MCP tools without blowing up my context window?

Enterprise agents often connect to hundreds of tools across cloud infrastructure, databases, and payment APIs—preloading these schemas conventionally burns 40,000+ tokens before you even type a prompt. Titan Mem features an autonomous native tool router. Instead of exposing every tool continuously, Titan Mem matches your intent against your organization's tool catalog in under 30 milliseconds, injecting only the exact 2 or 3 tools needed for the immediate step. You get the power of an entire enterprise toolchain with a verified 99.7% reduction in token overhead.

Does Progressive Disclosure (<150 tokens) break LLM Prompt Caching? What about tool call overhead?

It protects your prompt cache from active schema bloat. LLM providers (Anthropic Claude, OpenAI, Gemini) use prefix caching: identical static prompt prefixes receive a 90% discount. While modern IDEs like Claude Code automatically compact past chat history, they cannot compact away active tool schemas. If an agent connects to 200+ enterprise MCP tools, that ~48,000-token schema payload must sit in the prompt on every turn, incurring massive cache-read fees and eating 25% of your context window.

The Honest Math on Tool Calls: In a real-world workflow, an agent should never poll memory on every single turn (doing so would waste output tokens and round-trips). Instead, Titan Mem operates strictly Just-In-Time (JIT):

• Static Schema Elimination: Titan Mem acts as a local meta-router, shrinking the static prompt overhead from ~48,000 tokens down to a single lightweight tool definition (~140 tokens). This alone eliminates 99.7% of permanent schema bloat.
• Minimal JIT Invocations: In a typical session, memory search is called only 3 to 5 times—specifically when an unfamiliar API is requested or an error occurs. 5 queries $\times$ ~140 tokens adds less than 1,000 tokens of total session overhead, while preventing hours of manual re-debugging.
• Cross-Session Persistence: When a session ends, IDE auto-compaction memory is wiped clean. Titan Mem stores verified fixes permanently in local SQLite, ensuring you and your team never re-debug the same bug twice.

Net Result: 99.7% reduction in static schema overhead, zero round-trip waste, and permanent cross-session recall.

Why use Titan Mem instead of a cloud decision model like Jev or external tool routers?

Developers are raving about "System 1" decision models (like TypeSafe's Jev) because nobody wants to waste 45,000 prompt tokens on an LLM just to pick an API to call. But Jev is still a third-party cloud service that adds network hops and privacy exposure. Titan Mem performs local, in-process System 1 routing on your machine before the LLM ever sees the prompt:

Do I or my team have to restart our IDE when new memories sync?

No. Restarting IDEs and losing open tabs is completely unacceptable. Titan Mem runs with SQLite Write-Ahead Logging (WAL) concurrency. When team rules or multi-device deltas sync in the background, active Claude Code, Cursor, and terminal sessions detect new rows on their very next query—with zero IDE restarts and zero prompt latency.

How do I use "Remember this fix"? Do I have to type complex JSON commands or install git hooks?

Never. You don't type JSON and you don't install git hooks. You simply tell your agent in natural English during any chat: "Remember this fix: [description]". The agent automatically resolves the active Git commit hash (via git rev-parse --short HEAD) and touched file paths, storing the rule in SQLite via MCP. To make it completely autonomous, add a 2-line directive to your repository's CLAUDE.md or .cursorrules, and your agent will capture lessons after successful debugging turns automatically.

How does Titan Mem prevent prompt bloat?

Conventional agents dump entire files, long rule lists, and chat history into every turn, causing prompt bloat and massive API bills. Titan Mem keeps your system prompt lean (~400 tokens) and hydrates matching rules just-in-time via sub-3ms MCP search only when relevant.

What happens to my data if I uninstall?

Nothing happens to your data. The uninstaller removes only the binary and client configurations. Your SQLite database at ~/.titan/mem/memory_graph.db is preserved untouched. You can inspect it anytime with standard SQLite tools.

Do you send my code or memories to an external server?

No. Titan Mem runs completely locally on your machine. In the free Community tier, network egress is literally non-existent. In the Pro tier, cloud sync is End-to-End Encrypted (E2EE) with zero-knowledge keys—we cannot read your memories even if subpoenaed.

Why native Rust instead of Python?

Python engines require heavy virtual environments, 150MB+ runtimes, and introduce 200ms–800ms cold start delays. Titan Mem is compiled into a single static native binary that launches in 2.9ms, consumes under 15MB of RAM, and runs with zero external dependencies.