HireIQ vs TetherDust

HireIQ and TetherDust 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.

HireIQ

The scraped page provided does not match the tool data supplied: the source content describes Spotter, a travel-identification app, not a hiring platform. No factual claims about this tool's workflow, integrations, or production behavior can be sourced from the available evidence. What the validator context confirms: this is a commercial SaaS hiring platform offering AI-generated interview questions, candidate fit scoring, and structured feedback collection for hiring teams. Without a matching source page, production-level detail — API behavior, note-taking depth, scoring methodology — cannot be responsibly described.

TetherDust

TetherDust runs inside your infrastructure, connecting MCP servers to your codebase and database documentation so agents generate SQL that can be checked against the actual schema — not guessed. The core workflow chains natural language input through containerized agents that produce SQL, d3.js dashboards, and schema-to-code dependency maps, all inside strict read-only query boundaries. Scheduled reports ship by email or download without exposing write access. RBAC and audit logging are included for teams where data access needs a paper trail. The ceiling appears when you need write operations, or when your branching query logic outgrows what the agent layer can express without custom extensions.

Attribute	HireIQ	TetherDust
Pricing	Paid	Free
Price	€99/month	—
Free trial	7 days	No
Open source	No	Yes
Has API	Yes	Yes
Self-hosted option	No	Yes
Platforms	Web-based SaaS	Docker, self-hosted
Pros	Role-specific interview question generation tailored to candidate experience level, so interviewers stop winging questions for senior hires and asking junior-level questions of principals. Centralized feedback collection across all interviewers, which means the hiring decision is based on the full panel's structured notes rather than whoever talked loudest in the debrief. AI-driven candidate fit scores for side-by-side comparison, so the final shortlist conversation starts from data rather than gut feel — reducing the risk of the most-recently-interviewed candidate getting a halo effect. API availability, so teams with existing tooling can push candidate data in or pull scores out without being locked into the platform's UI for every step. Automated interviewer feedback on technique, which means less-experienced hiring managers get coaching without requiring a dedicated recruiting ops function to review every panel.	Documentation-grounded SQL generation verifies queries against your actual schema before they run, so hallucinated column names and wrong table joins surface before they reach your database. Full self-hosting via Docker Compose with enforced read-only query boundaries, which means you can deploy on air-gapped or private infrastructure without sending query logic or schema details to an external service. RBAC and audit logging are included at the platform level, so every AI-generated query access is traceable — without this, teams typically bolt on audit layers after a compliance incident. Schema-to-code dependency mapping updates as schemas evolve, so developers can see the downstream code impact of a migration before it ships rather than debugging broken queries after the fact. Provider-agnostic multi-agent support through MCP servers, so swapping the underlying LLM is an infrastructure configuration change rather than a code rewrite.
Cons	No self-hosted deployment option exists, so any team with data residency obligations — healthcare, finance, public sector — cannot use this platform and will move to a competitor that offers on-premise or private-cloud installation. The full feature set is behind a paid tier, and the free access window is time-limited — teams that need to pilot across a full hiring cycle before committing budget will hit that ceiling mid-process and face a forced decision before they have enough signal. Without confirmed ATS integrations, teams already running Greenhouse, Lever, or a similar system will maintain two parallel records — one in the ATS, one here — which defeats the centralization benefit and adds data hygiene work the platform was supposed to eliminate.	Read-only query boundaries are enforced by design — any workflow requiring write-back operations, data mutations, or ETL pipelines hits a hard architectural wall, and teams with those requirements move to a database-native AI tool or build a parallel pipeline outside TetherDust. Dashboard output targets d3.js specifically, which means customizing visualizations beyond what the agent generates requires direct JavaScript work; teams expecting a drag-and-drop editor or chart type flexibility will find the output layer thin and reach for a dedicated BI tool instead. The repository has 4 stars and 9 commits at time of curation — community support, third-party integrations, and documented edge-case handling are sparse, so teams hitting undocumented failure modes are writing the answer themselves rather than finding it in a forum. Complex multi-step conditional query logic — branching based on what one agent returns before passing to the next — pushes past what the agent graph handles natively; teams building those workflows add a Python orchestration layer, and at that point they are maintaining TetherDust plus a second system they own entirely.

Bottom line

HireIQ is paid while TetherDust is free; TetherDust is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between HireIQ and TetherDust?

HireIQ is Paid, while TetherDust is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is HireIQ better than TetherDust?

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.