FAQ
Product Positioning
Can I use Lantide Data if I don't know SQL or Python?
Yes. You can describe the analysis you need in plain language, and Lantide Data helps generate a Plan and SQL before execution. You review the direction and results, without writing code from scratch.
→ Quick StartIf general AI chat tools can analyze CSV files, why do I still need Lantide Data?
General chat usually produces a one-off answer. Lantide Data preserves the analysis as a reviewable Plan, verifiable SQL evidence, a Report, Source Run, and data lineage. Data and queries stay in the local workspace, so you can revisit definitions, understand dependencies, and continue the work later.
→ Why Analysis Conclusions Can't Stay in ChatI already use Claude Code or Codex. When do I need Lantide?
You do not have to replace your preferred Agent interface. When an analysis needs a formal Plan and evidence review, metric changes, historical investigation, lineage-based reruns, or a handoff, Claude Code or Codex can use Lantide through MCP Server while leaving the Plan, Report, SQL evidence, and Activity in a traceable workspace.
→ External AI Agents and MCP ServerSome cloud AI tools can connect to Google Drive or external databases. How is Lantide Data different?
The core difference is where data and computation live. Lantide Data is local-first: DuckDB reads, queries, and caches data on your machine, while external databases are integrated through a local query layer. This reduces data exposure, upload delay, and cloud timeout risk.
→ Where Lantide Sits in Your Data ArchitectureWhat mechanisms are included in Lantide Data’s Harness?
Lantide Data’s Harness includes state machines, domain tools, context engineering, IDE integration, and the local data plane. Together, these mechanisms control when AI can draft, query, execute, and deliver, turning analysis from a one-off answer into a reviewable, repeatable workflow.
→ AI AssistantExternal Agents and MCP
What is the difference between MCP Server and MCP Sources?
They run in opposite directions. MCP Server lets external Agents such as Claude Code and Codex connect to Lantide, use its local analysis environment, and leave reviewable artifacts. MCP Sources lets Lantide connect to external data or APIs and materialize the results as queryable tables.
→ Connect External AI Agents to Lantide SafelyCan Claude Code or Codex operate Lantide without an LLM API Key?
Yes, through the external Agent + MCP Server path, which does not require an additional LLM API Key in Lantide. The external Agent still operates under its own subscription and MCP support terms. Lantide's built-in Agent still requires your own LLM API Key or another configured model endpoint.
→ External AI Agents and MCP ServerSkills
Does Lantide support Skills, and can a Skill grant more Agent permissions?
Yes. You can import methods into the Skill Library, explicitly load them with “/” in built-in chat, and optionally Share with external agents. A Skill provides guidance, not tool authorization: it cannot raise the MCP access mode or bypass Plan approval or audit.
→ Skills (Skill Library)Workflow
How is Plan → Approve → Execute different from asking AI to write a plan first?
In general chat tools, that is mostly a prompt-level agreement. Lantide Data makes it a product-level engineering boundary: during Plan, AI can draft but cannot start formal analysis; only humans can press Execute. The approved Plan is locked and recorded for review and traceability.
→ Plan → Annotate → Execute → ReportWhat is the difference between Quick and Project Analysis?
Quick Analysis is for ad hoc queries and lightweight SQL Q&A. Project Analysis is for formal work that needs a Plan, annotations, Execute, and Report. You can choose based on complexity instead of starting every question as a full project.
→ Quick Analysis vs Project AnalysisCan I rerun an analysis in the correct order after the data changes?
Yes. Lantide Data records data lineage and DAG dependencies between analysis steps. After data or a query changes, Source Run can rerun intermediate caches and downstream results in dependency order. The system provides a repeatable execution path, while people still review the final definitions and results.
→ Cache and Source Run: What Analysts Need to KnowWhen a departing analyst leaves behind a pile of Skills, Markdown, HTML, and SQL that even an AI Agent struggles to untangle, how is Lantide different?
In a general AI analysis environment, project context is often scattered across chat history, Skills, Markdown, HTML, notebooks, and multiple SQL versions. The next person has difficulty taking over, while Agents such as Claude Code and Codex must read many files and infer their relationships—consuming context tokens and increasing the risk of missed definitions or references to the wrong version. Lantide preserves the Plan, Report, SQL evidence, Source Run lineage, and Activity in a project structure that people can inspect directly and Agents can retrieve selectively through Lantide-specific resources and tools. This reduces unnecessary context loading and unsupported guesses. If upstream data was deleted or overwritten, reproducing the exact result still depends on whether the original data was retained.
→ .lantide Export, Import, and RebindingHow can I share analysis results with managers or clients?
Formal analysis produces a Report with methods, findings, evidence, and recommendations. You can also generate a standalone HTML report for browser-based presentation, export it as PDF, or share it with non-technical stakeholders, reducing copy-paste and reformatting work.
→ Report to HTML: Weekly Meetings and TweaksMemory
Will knowledge be recorded randomly? How do we keep definitions consistent?
No. New rules extracted from conversation first enter Queued Knowledge and are only injected into AI context after approval by a manager or authorized member. This keeps business definitions and metric logic consistent across the team and AI assistants.
→ Agent Memory vs Plan: Don't Mix Them UpCan I disable memory?
Yes. Agent Memory has a master switch and can be fully disabled for specific projects or compliance needs. When disabled, AI will not write new knowledge or inject it into context, which is useful for sensitive or tightly controlled analysis.
→ Agent Memory (Knowledge Base)Technical
What data formats are supported?
Lantide Data supports local CSV, Excel, and Parquet files, using DuckDB as the unified query layer. Common data files can be placed directly into the workspace and quickly mapped into queryable tables.
→ Welcome to Lantide DataMust I download data as files, or can I use company databases and external data services?
Files are not required. In addition to local CSV, Excel, and Parquet files, Lantide Data can query PostgreSQL, MySQL, SQLite, and other databases through DuckDB ATTACH, or use MCP Sources to materialize external data and API results as queryable, refreshable tables.
→ Data Browser and Data SourcesIf data stays local-first, how does AI work?
Lantide Data lets AI help understand the question and generate a Plan / SQL without sending raw data to the cloud. The system provides schema information, such as column names and data types; actual queries and computation return to your local workspace and run through DuckDB.
→ AI AssistantCan the AI assistant accidentally modify or delete my Excel, CSV, or database files?
No. Lantide Data includes a SELECT-only read guard and Harness safeguards. In the workspace, AI can only read data and create temporary computation caches; it cannot modify, delete, or overwrite your original files.
→ Backup, Security Boundaries, and TroubleshootingDo I need internet?
Local queries do not require internet, and data processing runs inside your workspace. AI features can call your configured LLM API; enterprise teams can also use self-hosted endpoints or Ollama to keep usage fully inside their own network.
→ AI AssistantWhat is BYOK?
BYOK means configuring your own LLM API Key for Lantide's built-in Agent, giving you control over model choice and usage costs. If you use an external Agent such as Claude Code or Codex through MCP Server, you do not need to configure an additional LLM API Key in Lantide; the external service's own plan still applies.
→ AI AssistantDownload
Is the full version free?
Yes. Lantide Data's full desktop version is available at no cost. Contact us if your organization needs a tailored enterprise deployment or integration.
→ DownloadWhich operating systems are supported now?
Lantide Data currently supports macOS 12+ and Windows 10+. You can choose the installer for your platform on the download page; future platform support will also be updated there first.
→ Installation & SetupHow do I get started after downloading?
After installing the app, create or select a local data workspace, add CSV, Excel, or Parquet files, and follow Quick Start to run your first analysis. We recommend starting with a small dataset to learn the Plan → Execute flow.
→ Quick Start