Accelerate recruiting and hiring
Organize candidate information, prepare job descriptions, and support recruiting workflows.
A drag-and-drop platform for building AI agents that process documents, with security features aimed at regulated industries.
Stack AI is a drag-and-drop platform for building AI agents, organized around three modules: agents, workflow logic called Flow, and data handling called Storage. It can process unstructured documents along with text, image, audio, and video inputs, and agents can connect to sources like Google Drive and Notion. Users deploy agents as a Slack bot, a Chrome extension, or through a REST API for custom integrations. Stack AI states it meets SOC 2, HIPAA, and GDPR requirements, offers single sign-on, and has signed data protection agreements with both OpenAI and Anthropic covering how those model providers handle data sent through Stack AI.
This fits a team in a regulated industry, such as healthcare or financial services, that needs to build document-processing agents while keeping data handling agreements with the model providers. A free plan with 500 monthly runs, two projects, and one seat is enough for an initial technical evaluation. Beyond the free plan, published pricing jumps straight to a custom Enterprise plan, so a larger pilot may need a sales conversation; ask specifically about run limits and seat costs at your expected volume, since the public page shows no mid-tier plan. As with any document-processing agent, test accuracy on real document formats before trusting it with sensitive records.
Potential matches to review against your requirements. Explore matching tools or read a task guide before you choose.
Organize candidate information, prepare job descriptions, and support recruiting workflows.
Turn approved content and customer requirements into proposal drafts for your sales team.
Find answers across your documents and internal resources.
Bring key business metrics together in dashboards and summaries for leadership.
Use historical trends and business data to plan for future customer demand.
Plan production around orders, available capacity, materials, and delivery deadlines.
Identify bottlenecks and support frontline teams with clearer work instructions and operational insights.
Balance stock availability with demand to reduce shortages and excess inventory.
Use equipment data to spot potential issues and plan maintenance before breakdowns.
Find relevant answers, route requests, and help service teams respond to customers sooner.
Analyze spending, compare suppliers, and identify opportunities to improve purchasing.
The industries and leadership roles this tool is most often matched with.
How one company factor at a time moves the modeled score. The published score is unchanged.
These estimates cover licensing, setup, integrations, staff time, security, administration, and support.
| Cost measure | Low | Base | High |
|---|---|---|---|
| First-year total | $57.8K | $91.9K | $149.2K |
| Three-year total | $121.4K | $184.7K | $288K |
| First-year cost per unit | $57.8K | $91.9K | $149.2K |
| Average annual cost per unit (over three years) | $40.5K | $61.6K | $96K |
| Component | Low | Base | High |
|---|---|---|---|
| Licensing and usage | $16.5K | $22K | $29.7K |
| Implementation | $9.6K | $16K | $27.2K |
| Integration | $12.1K | $22K | $39.6K |
| Staff time and change management | $6.3K | $9K | $12.6K |
| Security | $4.9K | $7K | $10.5K |
| Administration | $3.8K | $5K | $6.8K |
| Support | $1.9K | $2.5K | $3.4K |
Estimate assumptions: This scenario uses a category-based allowance, not a verified price for this product. Based on 1 production deployment. Confirm the vendor’s billing unit and current price or quote before budgeting.
Benefits have not been estimated: The current research does not estimate potential savings, return on investment, or how long it would take to recover the cost. Earlier benefit estimates are excluded.
Confirm current product identity, commercial packaging, data processing terms, sign-in and access rules, retention, integrations, support model, implementation effort, and rollback conditions.
Verify identity, package, availability, ownership, pricing, and security evidence before approving a pilot
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
Define what success looks like for a test of Stack AI and assign someone to lead it.
Once the requirements above are met, compare a small trial with how your team works today.
Track adoption, output quality, business results, and actual costs against the estimate.
Use the results to decide whether to stop, adjust, or expand the pilot.
Confirm encryption, how the vendor uses your data, customer data separation, how long data stays and how to delete it, activity records, sign-in and user setup, where data is handled, other companies that process data, past incidents, and what your team must manage.
Export agent definitions, prompts, tools, schemas, code, memory design, evaluation sets, traces, schedules, approvals, and deployment configuration from Stack AI. Business logic is most portable when it remains in standard code and APIs; managed runtimes, connectors, memory, and observability may need rebuilding, so run parallel regression tests before redirecting traffic. The catalog status is “Active | acquired May 2026”; confirm renewal, support, successor-product, and migration rights before further commitment.
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
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Research observations recorded: 1. Evidence quality: Good support.
Recorded score and category rank across research updates.
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