SiftHub

Breadth across classes, and the design assumption is that the customer's stack is untidy. Knowledge sources: Google Drive, Slack, Notion and connected apps, searched in place rather than migrated into a library first. Signal sources: CRM, calls and inbox, read continuously to drive proactive output. Delivery: embedded inside Word, Excel, Google Docs and Slack so responses happen where the work already happens, plus the web app.

Connectors are described as out of the box with customizable options, so the set is extensible by configuration. That spans document storage, wikis, collaboration, CRM, conversation and email, which is spread rather than depth in one ecosystem. Every one of those surfaces is a connector SiftHub built, with no public API or webhook for a customer to build their own.

Sourcesifthub.io/agents/rfp-agent and sifthub.ioread 2026-09-04

A chain that starts before drafting and continues past submission. The RFP Agent reads the full intake document, including appendices, buried requirements and deadlines scattered across pages, and produces a structured checklist of milestones, mandatory submissions and recommended attachments before anyone writes anything, which is planning rather than extraction.

Drafting then runs from approved content across the connected stack, validation gates the output, exceptions route to named experts with chasing reminders, and review closes the loop. Beyond responses the same orchestration produces meeting briefs, battlecards, deal briefs, collateral and follow-ups from detected signals, so the platform runs a deal-cycle chain rather than a document chain, which is the vendor's stated positioning and is borne out by the artifact set.

Sourcesifthub.io/features/ai-rfp-software and sifthub.io/agents/rfp-agentread 2026-09-04

Retrieval over the customer's connected sources with attribution. A retrieval-augmented pipeline with fine-tuned embedding models and cross-encoders searches Google Drive, Slack, Notion, SharePoint, Salesforce, Gong and the other 15+ connectors in place, grounds every response in approved content and traces each answer to a document, its owner and its last-modified date; customer data is not used to train models.

Sourcesifthub.io and sifthub.io/blog/sifthub-soc2-type-ii-compliantread 2026-10-01

A shipped approval step and exception routing. The home page states human review and approval workflows run before anything is sent externally, and exception based routing sends only the questions that need expert input to the right subject matter expert with persistent reminders, under fine grained permissions.

Sourcesifthub.io and sifthub.io/agents/rfp-agentread 2026-10-01

Attested compliance and a documented access surface. SOC 2 Type II is attested against the AICPA Trust Services Criteria, alongside ISO 27001:2022 and VAPT certification, which SiftHub describes as a triple layer covering enterprise procurement, financial services, healthcare and other regulated sectors, with the full SOC 2 Type II report and supporting documentation obtainable under a mutual NDA. Fine grained permissions over content and responses are documented on the product pages.

Data handling is stated specifically rather than generally: customer data is not used to train models, every output is grounded in the customer's own connected sources, and every answer is source-attributed to a document, an owner and a last-modified date, with those controls stated to be inside the scope of the SOC 2 Type II audit, which puts the AI behavior inside the attestation boundary. No trust center or compliance portal is published, so the report comes on request under NDA rather than self serve; the pricing page lists SSO, SAML and custom roles on the full platform, and no SCIM is documented.

Sourcesifthub.io/blog/sifthub-soc2-type-ii-compliant and sifthub.ioread 2026-09-04

Attribution on the answer and a trail over the content, no record of the agent. Answers carry document, owner and date attribution and confidence scores, the pricing page lists advanced analytics on the platform, and governance trails cover the response lifecycle. Nothing records what an agent read before choosing a passage or why it routed a question.

Sourcesifthub.io and sifthub.io/pricingread 2026-10-01

A governed content repository, not memory. Approved answers and past responses persist with owners and last modified dates as knowledge content; no memory the agents keep and read back as their own state, with a scope, lifetime or delete path, is documented.

Sourcesifthub.ioread 2026-10-01

Multi tenant cloud with no location or topology control offered. No region selection, EU or other in region option, private cloud, VPC, single tenant tier or on premises route is published, and the security announcement names three certifications and the training boundary without naming a hosting region. That gap stands out because the platform is sold partly for answering security questionnaires for enterprise procurement, financial services and healthcare buyers, and residency is a routine line in the documents it exists to complete.

Sourcesifthub.io/blog/sifthub-soc2-type-ii-compliant and sifthub.ioread 2026-09-04

A named set of prebuilt agents, each doing its own job. The home page lists the Battlecard Agent, RFP Agent, BuyerIQ Agent, Answer Agent and Search Agent, and the pricing page sells the RFP Agent on its own as a point solution beside the full platform, so each stands without the others.

Sourcesifthub.io and sifthub.io/pricingread 2026-10-01

Deal signals start the agent's work on their own. SiftHub detects signals across CRM, calls and inbox and produces meeting briefs, battlecards and follow-ups because something happened rather than because a person asked; RFP intake and delivery inside Word, Excel, Google Docs and Slack sit beside it.

Sourcesifthub.io and sifthub.io/agents/rfp-agentread 2026-10-01

The customer does not choose the model and no provider is named. No model list, routing policy, per workspace selection or bring your own key option is published; the security announcement is the closest the vendor comes to describing its AI architecture. The vendor does state that customer data is not used to train models and that every output is grounded in the customer's own connected sources, with those controls inside the SOC 2 Type II audit scope; that is a data boundary rather than model choice.

Sourcesifthub.io/blog/sifthub-soc2-type-ii-compliant and sifthub.ioread 2026-09-04

An MCP server the vendor offers, with little published about it. sifthub.io/mcp describes SiftHub MCP bringing deal intelligence into Claude, ChatGPT and other MCP clients over OAuth 2.0 with SSO. No endpoint, no tool list and no statement that any tool creates or changes SiftHub objects is published, and no API, SDK or webhook surface is documented.

Sourcesifthub.io/mcpread 2026-10-01

A scored quality gate on every agent answer. Multiple validation checks with customized confidence scoring run before any answer reaches a customer facing screen, and where no reliable answer exists the system returns that no answer was found.

Sourcesifthub.ioread 2026-10-01

Embedding is not operating. SiftHub runs inside Word, Excel, Google Docs and Slack through those applications' own add-in frameworks, which is authenticated application integration on surfaces the customer has licensed, not an agent driving software with no programmatic interface.

Everything else moves through connectors to Google Drive, Slack, Notion and connected apps, and through CRM, call and inbox signal reads. No browser extension, portal autofill, headless session, screen or click automation is documented.

SiftHub covers questionnaires by working inside the customer's own editor rather than filling them inside third party procurement portals, and portal submission is not described.

Sourcesifthub.io/solutions/rfp-software and sifthub.ioread 2026-09-04