QueryPie AI
QueryPie AI is an agentic AI platform bundling a governed MCP gateway, centralized access control, and pre-built AI agents for enterprises.
QueryPie AI makes sense when your AI rollout is blocked on the question "what did the agent touch, and who approved it?" The governed MCP gateway, ACP's centralized authorization across databases, Kubernetes and web apps, and audit logs are the actual product — the six pre-built agents are how you demonstrate value while the governance layer proves out. It is not a model-quality play: the homepage runs on Claude Sonnet 4.6, so you're buying control plane, not intelligence. Teams without a governance function, without Kubernetes, or without production data sources will spend more time wiring than working; the free start tier is a reasonable way to test the agent UX before committing. If your
Verified 7d ago · liveness 62/100 · cite: rightaichoice.com/tools/querypie-ai
- Enterprise IT and platform teams deploying AI agents against production databases and systems
- Security and compliance teams at regulated firms (finance, healthcare, government) needing audit-ready records
- Sales and operations teams automating quotation processing, email-to-PDF conversion, and document review
- Organizations running Kubernetes and multi-cloud infrastructure that want access control unified
- Individuals or hobbyists who just want a standalone AI chatbot
- Small teams with no existing databases, Kubernetes, or access-review process to govern
- Buyers who want out-of-the-box AI with zero configuration or custom agent work
We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.
- Honest verdict, not marketing
- Real pros & cons from real users
- Attributed quotes with receipts
3 free scans · no card needed
Skip QueryPie AI if you want a standalone chatbot or a single agent on one database — the governed MCP gateway, ACP access controls, and audited agent runs only pay off once you have production data sources and someone accountable for access review.
Usage-based LLM deployment on AIP means model spend scales with agent activity, so a busy Data Analysis or Document Review workflow shows up as variable cost rather than a flat seat fee.
QueryPie's published starting point on the vendor site is a free start option with access to AIP chat, the pre-built agents, the governed MCP gateway, My Drive, and the Skills and Apps marketplace. That entry point suits a pilot; the cost that follows is usage-based LLM deployment on AIP plus FDE-built custom agents. Budget-holder comparisons should be against governance and access-control platforms rather than per-seat AI chat subscriptions.
In short
QueryPie AI — QueryPie AI is an agentic AI platform bundling a governed MCP gateway, centralized access control, and pre-built AI agents for enterprises. Best for Enterprise IT and platform teams deploying AI agents against production databases and systems, Security and compliance teams at regulated firms (finance, healthcare, government) needing audit-ready records, Sales and operations teams automating quotation processing, email-to-PDF conversion, and document review. Free to use.
What's new in QueryPie AI
Checked 7 days agoAcross the latest 4 updates: 4 news mentions.
[Part 2] ISO/IEC 42001 — Where Do I Even Start? What Comes First?
Part 2 of QueryPie's ISO/IEC 42001 guide covers how to inventory AI assets and evolve that inventory into an AI Control Tower.
What is an FDE (Forward Deployed Engineer)?
QueryPie explains the forward deployed engineer role in the generative AI era, the skills it requires, and how it differs from IT consultants and SES.
[Part 1] ISO/IEC 42001 — Where Do I Even Start? What Comes First?
Part 1 of QueryPie's practical starting guide for ISO/IEC 42001 certification, covering scope definition and stakeholder identification before building an AI management system.
AI Work OS: How a new intelligence works within an enterprise
QueryPie outlines the AI Work OS concept: enterprise context for AI, an execution structure for real tasks, and controls to govern that execution.
What people actually say about QueryPie AI — is it worth it?
We scanned public community sources for QueryPie AI on Sep 22, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 0 of the posts we fetched could be positively tied to QueryPie AI. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is QueryPie AI? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Governed MCP gateway with centralized management, visibility, policy controls, and audit logs
- Pre-built agents: Data Analysis, Report Writer, Quotation Assistant, Sales Insight, Document Review, MCP Automation
- Access Control Platform (ACP) centralizes authorization for databases, systems, Kubernetes, and web applications
- Usage-based LLM deployment on the AI Platform (AIP)
- Chats running on Claude Sonnet 4.6 per the vendor homepage
- Forward Deployed Engineers (FDEs) build customized AI agents for enterprise workflows
- Lingo: AI real-time interpretation and subtitling for Google Meet, Zoom, Teams, and in-person meetings
- NotePie: AI learns from uploaded documents or web links and converts them into structured data
- Email-to-PDF quotation processing with line-item parsing and charting
- My Drive for file storage
- Skills and Apps marketplace for extending agents
- Edge Tunnel for secure connectivity
- AI-powered access policies and anomaly detection in ACP
- Revenue dashboard analysis and support operations widgets
- Voice / voice conversation
About QueryPie AI
QueryPie AI is an agentic AI platform for organizations that want AI agents working against real company data with security and audit trails attached. It ships three pieces that teams usually stitch together: AIP (AI Platform) for usage-based LLM deployment and MCP gateways, ACP (Access Control Platform) for centralized authorization across databases, systems, Kubernetes, and web applications, and a set of pre-built agents you can run on day one. Those agents include Data Analysis, Report Writer, Quotation Assistant, Sales Insight, Document Review, and MCP Automation. A demo on the vendor's homepage shows Quotation Assistant reading today's inbox, finding an emailed quote titled "Software Supply Quotation," parsing line items (USD 37,500 license, USD 7,500 support, USD 3,750 implementation), charting the amounts, and saving a formatted PDF to the Desktop. Chats run on Claude Sonnet 4.6 according to the homepage interface. Beyond agents, the platform adds Lingo for real-time interpretation and subtitling across Google Meet, Zoom, Teams and in-person meetings, NotePie for turning uploaded documents and web links into structured data, Edge Tunnel, My Drive file storage, and a Skills and Apps marketplace. Forward Deployed Engineers (FDEs) build custom agents where the pre-builts don't fit — QueryPie published an explainer on the FDE role in July 2026. The company has also published multilingual DLP model research with NIPA GPU support, announced a partnership with Japanese AI consulting firm Ashisuto AI Terasu, and published a two-part ISO/IEC 42001 guide covering AI asset inventory and evolving into an AI Control Tower. This is governance-first infrastructure: it assumes you already have production databases, Kubernetes, and someone who owns access review.
Behind the Verdict
QueryPie's differentiator is that it treats the MCP gateway as a governed surface rather than a plumbing detail. The homepage is explicit: agents connect to enterprise tools and data through a gateway with centralized management, visibility, policy controls, and audit logs. That's the thing most agent stacks lack, and it's why the vendor positions ACP — access control for databases, systems, Kubernetes, and web apps — as half the platform rather than a bolt-on. The pre-built agent set is practical rather than flashy. Quotation Assistant is the clearest example: the on-site demo walks an inbox scan, a line-item parse, a chart, and a PDF written to Desktop, with the agent offering an executive summary or approval email as a follow-up. Data Analysis, Report Writer, Sales Insight, Document Review, and MCP Automation round out workflows that ops, sales, and finance teams already do by hand. Two adjacent products matter more than their billing suggests. Lingo does real-time interpretation and subtitling for Google Meet, Zoom, Teams, and in-person meetings — useful for multinational teams but a different buying center than the agent platform. NotePie turns uploaded documents and web links into structured data, which is the unglamorous input layer every agent deployment needs. Forward Deployed Engineers are the pressure valve: QueryPie published an explainer in July 2026 on the FDE role, and the homepage lists FDE services as a first-class offering, so custom agent builds are an expected part of the engagement rather than an exception. Where it fits: regulated and security-conscious buyers in finance, healthcare, and government, plus enterprise IT and platform teams who need an auditable trail for AI actions on production systems. The ISO/IEC 42001 blog series (Part 1 July 2026 on scope and stakeholders, Part 2 July 2026 on AI asset inventory and an AI Control Tower) shows the vendor is investing in the compliance vocabulary its buyers use. Where it doesn't: individuals who want a chatbot, small teams with no databases or access-review process to govern, and anyone optimizing purely on model capability. Deployment reads as web and API based — there is no on-premise option documented on the pages reviewed here — so buyers with a hard on-prem requirement should verify before committing. The honest framing is that this is infrastructure. Budget setup time for connecting data sources, defining policies, and getting your first audited agent run to completion.
Researching QueryPie AI? Get your full AI stack in 60 seconds.
Free, no signup — tell us your goal and get tools matched to your budget & existing stack.
Real-world workflow fit
Concrete scenarios for the personas QueryPie AI actually fits — and what changes day-one when you adopt it.
Inbound quotations arrive as email attachments and need to be parsed, compared, and filed. They run Quotation Assistant against today's inbox to find the attachment, pull the line items, chart the amounts, and save a formatted PDF.
Outcome: A quote like the demo's Software Supply Quotation (USD 48,750 across license, support, and implementation lines) becomes a structured PDF on the Desktop in one command, with an executive summary or approval email offered as a follow-up.
They connect ACP to databases, systems, Kubernetes, and web applications so authorization is centralized, then route agent traffic through the governed MCP gateway.
Outcome: Agent actions against production systems carry policy controls and audit logs, and access policies plus anomaly detection flag unusual activity rather than being reconstructed after an incident.
They load contracts, reports, and reference links into NotePie to turn unstructured material into structured data, then run Data Analysis and Report Writer against the result.
Outcome: Recurring analysis and reporting stops being manual copy-paste work, and the outputs remain traceable because they ran through the governed gateway.
Use Cases
- Automate data analysis and report writing by connecting agents to enterprise databases and systems.
- Process quotation emails: extract line items, chart the amounts, convert to PDF, and save with one command.
- Deploy governed AI agents that interact with MCP servers under centralized policy controls and audit logs.
- Secure access to databases, Kubernetes, and web apps with audit-ready governance across multi-cloud environments.
- Provide real-time interpretation and subtitles across Google Meet, Zoom, Teams, and in-person meetings.
Models Under the Hood
as of 2026-10-10
Limitations
- QueryPie is infrastructure, and it assumes infrastructure underneath it: databases, Kubernetes, and a real access-review process.
- The vendor's homepage and product pages describe deployment as web and API based with no on-premise option documented, so organizations with a hard on-prem requirement should confirm before committing.
- The pre-built agents cover common workflows — Data Analysis, Report Writer, Quotation Assistant, Sales Insight, Document Review, MCP Automation — but workflows outside that set go through Forward Deployed Engineers, which is a services engagement rather than self-serve configuration.
- Lingo covers meetings, but it is a separate product from the agent platform and serves a different buyer.
- NotePie is the input layer for documents and web links, so messy or unstructured source material still needs work before agents get useful output.
as of 2026-10-02
Verification history
We have re-verified QueryPie AI 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 7 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published QueryPie AI tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free Start
$0/mo
Ideal for
A pilot team that wants to test the pre-built agents and governed MCP gateway against a real workflow before committing to AIP deployment and FDE work.
What this tier adds
Starting tier: free entry point with AIP chat, the pre-built agents, the governed MCP gateway, My Drive, and the Skills and Apps marketplace.
Where the pricing makes sense
The company stage and team size where QueryPie AI's pricing actually pencils out — and where peers do it cheaper.
QueryPie's published starting point on the vendor site is a free start option with access to AIP chat, the pre-built agents, the governed MCP gateway, My Drive, and the Skills and Apps marketplace. That entry point suits a pilot; the cost that follows is usage-based LLM deployment on AIP plus FDE-built custom agents. Budget-holder comparisons should be against governance and access-control platforms rather than per-seat AI chat subscriptions.
Setup time & first value
How long it actually takes to get something useful out of QueryPie AI — broken out by persona, not the marketing-page minute.
For a team that already has databases and Kubernetes: expect hours to connect ACP and define initial access policies, then a first audited agent run the same day using the pre-built set. For a sales or ops team: Quotation Assistant on a mailbox is the fastest path to visible value. For organizations without a governance function or clean data sources: budget days to weeks, and expect a Forward
Switching to or from QueryPie AI
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From standalone AI chat tools: move the workflow into AIP chat, then add the governed MCP gateway so agent actions are logged.
- →From manual quotation handling: switch inbox quotation parsing, line-item extraction, and PDF generation to Quotation Assistant.
- →From scattered access spreadsheets: consolidate database, system, Kubernetes, and web app authorization into ACP.
- →From unstructured document stores: point NotePie at the documents and links so downstream agents work from structured data.
- ↗To a general-purpose AI chat tool: acceptable if you no longer need audited agent actions or governed MCP connectivity.
- ↗To point access-management tools: expected if the agent platform isn't the reason you bought ACP.
- ↗To bespoke in-house agent tooling: viable only if you're prepared to rebuild the gateway, policy controls, and audit logging yourself.
Integrations
Resources & Guides
Tutorials & Learning
![[QueryPie KAC] How to Connect to a Kubernetes via the QueryPie Agent](https://img.youtube.com/vi/AnhHnXdBM10/mqdefault.jpg)
[QueryPie KAC] How to Connect to a Kubernetes via the QueryPie Agent
QueryPie AI
![[QueryPie SAC] How to Connect to Servers via the QueryPie Agent](https://img.youtube.com/vi/Tmrm0seAGV0/mqdefault.jpg)
[QueryPie SAC] How to Connect to Servers via the QueryPie Agent
QueryPie AI
![[QueryPie DAC] How to Use the Web Editor](https://img.youtube.com/vi/yrGb8C7ltf4/mqdefault.jpg)
[QueryPie DAC] How to Use the Web Editor
QueryPie AI
YouTube returned 6 videos for “QueryPie AI”, and we withheld 2: 2 could not be judged, because “QueryPie AI” is a single word that other videos use for other things. Showing the 4 we can prove are about QueryPie AI.
Official links
Tools that pair well with QueryPie AI
Common stack mates teams adopt alongside QueryPie AI, with the specific reason each pairing earns its keep.
SailPoint
Enterprise identity governance for humans, machines, and AI agents, with adaptive access control and continuous risk assessment.
Pigment
Agentic AI agents embedded in an enterprise planning model on your governed data.
Olas Network
A decentralized network where you co-own autonomous AI agents that trade, hire each other and settle payments on-chain.
Featured Head-to-Head Comparisons
Querypie Ai vs Screenplayiq
QueryPie AI and ScreenplayIQ serve entirely different markets. QueryPie AI is an enterprise agentic AI platform for secure data and system automation, while ScreenplayIQ is a niche screenwriting analytics tool for box office prediction. Choose QueryPie if you need governed AI agents integrated with your infrastructure; choose ScreenplayIQ if you're a film professional seeking data-driven script feedback.
Querypie Ai vs Push Security
If your priority is deploying trusted AI agents with enterprise governance and data access control, QueryPie AI is the clear choice. If you need to secure your organization against browser-based attacks (AiTM, session hijacking, AI data leakage), Push Security is essential. They address different problems; select based on whether your immediate need is AI enablement or browser threat defense.
Querypie Ai vs Audioeye
QueryPie AI and AudioEye serve entirely different needs: QueryPie is for enterprises needing secure, governed AI agents to automate data analysis and workflows, while AudioEye is for organizations that must meet web accessibility compliance. Unless your primary concern is ADA/WCAG litigation risk, QueryPie offers broader value for internal AI adoption.
Alternatives to QueryPie AI
View all
SailPoint
Enterprise identity governance for humans, machines, and AI agents, with adaptive access control and continuous risk assessment.
Pigment
Agentic AI agents embedded in an enterprise planning model on your governed data.
Olas Network
A decentralized network where you co-own autonomous AI agents that trade, hire each other and settle payments on-chain.
Frequently Asked Questions
Best-of guides
Used QueryPie AI? Help shape our editorial sentiment research.