AI WorkDeck vs AnySearch

AI WorkDeck and AnySearch are both business tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

AI WorkDeck

Built on a LibreOffice core for Windows and macOS, AI WorkDeck combines document drafting, AI-assisted generation, citation verification, and due diligence review inside a single desktop application. Every AI output is traced back to its source sentence, so you can see exactly what the model cited before accepting a revision. The plugin marketplace — 29 Skills at the time of listing, contributed by legal practitioners and open-source community members — covers M&A due diligence, contract risk flagging, NDA triage, and witness examination prep. The community edition is AGPLv3 open-source and free to install; AI consumption services (transcription, OCR, LLM calls) are metered at cost plus a fixed markup. Firms that need to modify the code and keep it internal, or run closed plugins, need the paid commercial license.

AnySearch

The platform ingests MySQL, PostgreSQL, Oracle, and other sources, builds an OpenSearch-backed knowledge graph, and surfaces answers through a multi-agent search layer where a supervisor routes each query to specialized analyst agents — research, data, or reporting. Every query, record view, and login lands in an audit ledger that meets AEPD-grade compliance requirements, with AWS Bedrock guardrails redacting PII on the way out. Geospatial mapping, field-service KPI dashboards, and structured faceted filtering are pre-built surfaces, not custom builds. The ceiling appears at the integration layer: there is no self-hosted option, so teams with data residency mandates that prohibit cloud egress hit a hard wall before they get to the demo.

Attribute	AI WorkDeck	AnySearch
Pricing	Paid	Paid
Price	From ¥39,800 / year	—
Free trial	No	No
Open source	No	No
Has API	No	Yes
Self-hosted option	Yes	No
Platforms	Windows, macOS	Web, iOS, Android
Pros	Local-first data handling with no mandatory cloud document upload, so files subject to attorney-client privilege or NDA stay on the machine and never touch a shared server. Sentence-level AI output attribution that links each drafted clause back to its source document, which means a supervising attorney can verify AI reasoning without reading every citation manually. Pre-built legal Skills (contract risk review, M&A due diligence, citation verification, witness prep) installable from the community marketplace, so a firm without in-house developers gets domain-specific AI workflows without building from scratch. LibreOffice core with tracked-changes support, so AI-suggested revisions appear as standard markup that any attorney can accept, reject, or annotate using the same review flow they already know. AGPLv3 open-source community edition, so teams can audit the codebase before trusting it with client documents — a step that is skipped with most closed SaaS legal tools.	Multi-agent supervisor routing sends each plain-language query to a specialized analyst agent, so a support rep asking 'which fiber installs missed SLA this month in the North region' gets a cited, structured answer instead of a list of documents to read manually. Tenant isolation is enforced at the infrastructure level — dedicated index prefixes and RBAC scopes per customer — which means a misconfigured permission does not create a cross-tenant data leak the way a purely policy-based system can. AEPD-grade audit logging captures every login, record view, and AI prompt with actor, IP, tenant, and outcome, so compliance reviews do not require reconstructing activity from scattered application logs. Pre-built field-service analytics surfaces — installation maps, contractor leaderboards, technician KPIs — answer 'where, who, how fast' without requiring a data warehouse join, so operations managers get answers in seconds rather than waiting on a BI team. Provider-agnostic data source connectors (MySQL, PostgreSQL, Oracle, and others) mean the platform indexes what you already have, so there is no requirement to migrate data before the first query works.
Cons	No API and no browser client means the tool cannot integrate with cloud document management systems, matter management platforms, or any existing firm tech stack — teams that need AI output to flow into their DMS hit a dead end and resort to manual copy-paste, which defeats the traceability benefit. Single-user desktop architecture makes real-time co-review impossible: two attorneys cannot work the same AI-assisted document simultaneously, and firms handling matters that require partner-associate parallel review end up routing documents through email or a shared drive outside the tool. The Skill marketplace is early-stage — the vendor page lists 29 Skills with install counts in the single digits for several modules, meaning community-contributed workflows have minimal field validation; a firm that discovers a Skill produces unreliable output on their document type has no fallback except filing a bug report and waiting. Teams whose compliance posture prohibits any third-party cloud calls — including the metered AI services for LLM, OCR, and transcription — face a product that is structurally incomplete without those services, and the vendor does not describe a fully air-gapped self-hosted model for the AI layer; firms in that position switch to on-premise solutions with local model support.	There is no self-hosted or on-premises deployment option: teams operating under data residency mandates that prohibit sending customer records to a third-party cloud cannot proceed past the architecture review, regardless of how strong the feature set is — at that point they move to self-hostable alternatives. The mobile apps for iOS and Android are in beta access per the vendor page, which means field-service workflows that depend on agents running queries on the road carry adoption risk until the mobile surface reaches general availability. Usage-based pricing with a Contact Sales acquisition flow means there is no self-serve way to validate cost at scale before committing; teams discover their actual bill only after negotiating a contract and running production traffic, which makes budget forecasting for variable-volume operations difficult.

Bottom line

Only AI WorkDeck can be self-hosted; only AnySearch exposes a public API; AI WorkDeck runs on Windows, macOS; AnySearch on Web, iOS, Android. Pick the difference that actually blocks you.

Frequently asked questions

What is the difference between AI WorkDeck and AnySearch?

AI WorkDeck is Paid, while AnySearch is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is AI WorkDeck better than AnySearch?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.