These are common questions about Cognaire Respond
Cognaire Respond is an AI-powered platform that automates responses to RFPs, security questionnaires, ESG, due-diligence forms, and complex multi-section assessments. Instead of relying on static Q&A libraries, Respond uses a retrieval-augmented multi-stage AI pipeline that generates tailored answers directly from your governed knowledge corpus. Respond has a focus on knowledge governance to maximize content quality, plus strong team collaboration tools, combined with a multi-layered approach to answer review, which maximizes answer quality and minimizes human effort.
Respond handles virtually any structured or semi-structured questionnaire, including:* RFPs, RFIs, RFQs* Security questionnaires, vendor risk assessments* Compliance checklists, DDQs, ESG, IT assessments* Sources can be custom spreadsheets, emails, PDF files, Word documents, and portal-based forms
For complex questionnaires, such as RFP responses, Respond uses a multi-stage workflow with the following stages:1. Upload and extract questions2. AI strategic analysis (business objectives, risks, win themes)3. Collaborative answering with bulk AI or quick AI, plus question assign-to-human and work management tools4. AI-powered quality review5. CV and case study selection (optional)Every answer is generated using your selected corpus → domain → unit → topics → types.Two AI passes are made: knowledge-grounded answer generation followed by a style & compliance pass using your language rules. Bid managers / respond administrators typically assign questions (with AI answers) to human reviewers in the third step described above. Then the assigned SMEs work in the streamlined My Questions screen which allows them to review and finalise AI-drafted answers quickly and efficiently.
* Proposal & bid teams* Sales engineers / presales* Security, risk and compliance teams* Legal & procurement* Delivery & professional services* SMEs contributing across multiple RFPs simultaneously* ESG, HR and recruitment professionalsRespond’s My Questions workspace is specifically designed for SMEs working across many bids.
Generic chatbots guess answers from public data. They have minimal team collaboration tools, no bulk processing, no risk scoring, no completeness scoring, zero progress reporting or dashboards, no auditing and generally use your company data to train their models.In contrast, Respond:* Includes bulk-answer capability that can answer 500+ questions in a single job* Only uses your secure governed corpus as an information source* Applies topic-level content rules (PII blocks, subtopic penalties, quality thresholds) to maximize corpus quality* Generates answers through a two-stage pipeline with completeness, compliance, and risk scoring* Uses extensive workflow and collaboration tools for assignments, teams, QA, approvals, and audit trails* Does not use your company data to train underlying AI models* Offers dedicated single-tenant deployment and single-country data sovereignty configurations as an optional add-on.This makes it suitable for enterprise-grade, compliance-sensitive responses.
Yes. Aside from RFPs, Respond can automate any large questionnaire including:* Security questionnaires* Environmental, social and governance (ESG) assessments* Vendor due-diligence (DDQ)* Compliance checklists* CV and case-study management* Internal assessments and capability documents* Grant applications
Only from your private, governed corpus. Respond never uses public internet data and never leaks your content to other tenants. Each customer operates inside an isolated subtenant.
Respond uses top-performing frontier LLMs through Amazon Bedrock. New models are released frequently and the solution is not tied to using the models from a single AI lab. As of December 2025, Claude models from Anthropic are used - however, Cognaire reserves the right to change to alternative models or providers as new ones are released. Cognaire has a comprehensive evaluation process that is invoked to test new models for performance and quality and ensure that new models match or exceed the performance of existing models.
Respond is deliberately designed to *not guess* answers. It prevents hallucinations using:* Strict grounding in your selected corpus* Source identification the underlying answer engine identifies all corpus sources used in its answers* Completeness scoring to flag weak answers* Topic-level quality controls that block non-compliant content from the corpus * Refusal patterns when the corpus lacks the required informationIf the corpus does not contain the answer, Respond avoids invention and flags the gap.
When content is present in the corpus, answers are typically extremely accurate because:* Knowledge storage is hierarchical (unit → domain → corpus), meaning that single documents can be shared across multiple areas of the solution* AI uses similarity search + topic/type filtering to narrow down to only the most relevant content for answering* Final answers are refined by a second LLM* Completeness checks ensure requirements are covered and helps human reviewers quickly identify incomplete answers* There is an additional deep AI quality assessment before submissionThe completeness metric can also be used to identify gaps in the corpus, which in turn can be used to identify knowledge improvement priorities. This supports a process of continuous improvement, leading to ongoing corpus development and improvement and ultimately more accurate answers in future.
Yes. Every AI-generated answer includes:* Completeness score (0–100%)* Risk rating (0–100%)* Compliance indicator (Yes, No, Partial, N/A)SMEs can sort and prioritise weak answers instantly.
No. Respond eliminates Q&A maintenance entirely. You only maintain documents, and AI derives answers from them.This dramatically reduces knowledge upkeep. This is a key differentiator compared to legacy proposal automation platforms and is only made possible due to recent advancements in AI.
Any content relevant to answering customer questions:* Product docs* Security policies* Architecture diagrams* Corporate content* Marketing materials* Case studies* CVs* Contractual language* Public website exports* SharePoint-synced documentsTopics and document types govern how they are used.
1. Corpus (top level)2. Domain (product group)3. Unit (product/module)Retrieval inherits upward automatically (unit → domain → corpus), reducing duplicate documents.
Respond includes an AI-powered Knowledge Reviewer that checks every new document for:* Quality* Relevance* Tone* PII* Blocked content* Topic penalties* Structural issuesHigh-quality documents are endorsed to human approvers; low-quality documents are rejected automatically.
Yes. Respond supports importing:* Legacy Q&A libraries (note: this is not mandatory, but works as a valid content source alongside other documents)* Spreadsheets* Document repositories (Word, PDF, text, Markdown)* Website content* CV and case-study libraries
Respond supports importing corpus knowledge content from:* Excel/CSV imports* Word and PDF documents* Markdown documents* Portal-style content (copy/paste)Respond supports importing questions from:* Excel spreadsheets, including large sheets with multiple tabs and complex structures* Question extraction from unstructured / semi-structured text using AIRespond supports exporting answers to various Excel spreadsheet, PDF and Word formats. Case studies and CVs can be exported to PDF format.
The base version of Cognaire Respond cannot answer directly inside tender / ESG / security or other portals. However, it does support question ingestion from portals via an AI-ingestion tool that allows it to extract questions from natural language.
Yes, Respond supports multi-language through:* Multi-language support for question-reading* Language rules request that answers are generated in a specific language* Language-specific CV and document tailoringThe application itself is only available in English, but corpus content, question-reading and answer-generation supports multi-language.
Two main tools:Stage 3 Answer Grid* Assign questions* Bulk answer* Review risk & completeness* Multi-user editing* Full audit historyMy Questions workspace* Cross-RFP SME work queue* Sort by status or similarity* Quick AI answering* Inline editing
Yes. Due dates can be assigned at both the overall questionnaire workflow document level and also the individual question level. Owners, statuses, analytics and bulk actions can be combined with due dates to manage and prioritize answering and the overall response.
Typical implementations range from a few days to a few weeks depending on:* Document volume* Corpus structure* Number of teams* Integrations (e.g., SharePoint, SSO)* Governance rules requiredIf you have an impending deadline for a submission - speak to us about how we can implement Respond in 1-2 working days.
No. Document upload, approval, AI answering, and workflows are all driven through the UI. Admins configure topics, types, corpus hierarchy, and model options. Everything in Respond is self-service and can be performed by business administrators.No coding is required. Only Sharepoint integration and single-sign on (SSO) may require some internal technical skills - but both are optional.
* Guided corpus setup* Review of topics, types, and governance rules* Workflow coaching* AI answering & QA training* CV/case-study module trainingThe above is provided both in the form of training sessions, videos and written material.The in-built Cognaire Assist agentic chatbot is available embedded within Respond and can also answer queries on how to use the application.
Respond is priced based on the application tier and number of users. Please speak to a Cognaire representative for further details. Request demo now
Pilots can be available on a case-by-case basis. Please speak to a Cognaire representative for further details.
Customers typically report:* 95 percent reduction in answer drafting time* 90 percentage reduction in overall finalized answer effort* Higher evaluator scores due to improved completeness and therefore addressing all points included in the RFP* Consistency across teams and regions* Reduced SME workload with reduced opportunity cost, allowing high-value experts to focus on other important work* Improved staff satisfaction and retention due to team members being freed-up to work on more mentally-stimulating and rewarding work than answering large questionnaires* Stronger compliance and lower response risk* Increased win rate and revenue
Yes. Respond’s governance-first design, subtenant isolation, topic-level content rules, and human-in-the-loop workflows make it a strong fit for:* Finance* Health* Government* Engineering* Enterprise B2B SaaSThis can be further boosted with optional add-ons such as single jurisdiction hosting (to avoid cross-border data transfers and AI inference) and dedicated tenant deployments.
Through layered controls:1. Governed corpus with topic/type rules to control the quality of knowledge sources2. AI corpus document assessment endorsing and scoring corpus documents before use3. Two-stage answering that separates answering from a post-answer improvement step4. Completeness, risk, compliance scoring metrics to aid human reviewers in focussing on the right answer5. Post-answer AI review stage across the whole answer grid to find contradictions, missing content, risk, and corpus gaps6. Human approval workflow via a comprehensive series of answer statuses
Yes. Respond's AI-augmented document approval rules are defined in terms of:* Status lifecycle* Human approvers* Topic-level routing rules* AI reviewer thresholds (quality, relevance, penalty/blocked subtopics)
Respond differs in four ways:1. No Q&A libraries – answers come from live knowledge, not stored snippets2. Two-stage AI pipeline – high-quality answers with brand-aligned style3. Governed corpus – topic/type rules, AI review, human approval4. SME productivity at scale – cross-document SME workspace, similarity sorting, analyticsCompetitors depend on static content libraries with high maintenance; Respond eliminates them entirely. Respond has a focus on maximizing answer quality thanks to AI-augmented knowledge controls. These controls protect the integrity of the underlying knowledge corpus by auto-rejecting low quality content and streamlining the final approval process for the centralized group of human content approvers. With this focus on answer quality, Respond also requires lower effort to finalize answers for customers. Once a comprehensive, well-structured corpus has been set-up, users of Respond can expect around 90% of questions to be answers that are around 90-95% quality. AI answers are often more consistent, comprehensive and accurate than human answers - and have zero grammar or spelling issues. This means that around 90% of AI-generated answers are often immediately ready for submission.
Roadmap is influenced by:* Customer feedback* New governance patterns* Support for more knowledge workflows* Expanded portal and CRM integrations* Enhanced strategic analysis features
No. Respond opts out of all training for third-party models. No uploaded content is used to improve any public model.Respond uses private inference via Bedrock, never public chat interfaces.
No. All data lives in a segregated subtenant with its own complete data storage including:* Corpus* Models* Vector indexes* Topics and types* Governance rules* API keys* Questions, Answers, CVs and Case StudiesThere is zero cross-tenant bleed in Cognaire Respond.There is also an optional add-on of a standalone deployment which means each customer of Respond has its own dedicated technology stack deployed (shared with no other tenants).
Respond inherits AWS-level controls plus its own governance features:* Encryption in transit and at rest* Strict RBAC with corpus and workflow-level permissions based on user roles* Topic-level AI review and blocking rules* Full audit logs and version history* Per-subtenant configuration and rate limits* Optional dedicated single-tenant deployment for regulated industries
Data is stored in the AWS region associated with your deployment.Dedicated-region or single-tenant deployments are available.
Yes. Respond includes per-user and per-permission controls for:* Corpus access* Document viewing/editing* AI usage rights* Bulk answering* Vector index access* CV/case-study modules* Admin capabilities
Yes. SharePoint document sync can be part of production deployments and automatically refreshes content every 24 hours (or manually on demand).
Yes. Cognaire Respond offers a secure API that allows an external organisation to integrate with the platform. The API includes dynamically answering questions based on the secure corpus, importing questions and populating the knowledge corpus.
Yes. Single-sign on (SSO) is supported by Cognaire Respond.
Cognaire Respond is primarily deployed in the United States, which is our default and most common hosting region. However, Respond fully supports regional deployments to meet data residency, regulatory, and AI sovereignty requirements for global customers.Respond can be deployed into various global locations, including (but not limited to): London, Frankfurt, Montreal, Sydney, Singapore or Tokyo.We also offer data sovereignty options that guarantee that your full application - including the corpus, AI job processing, LLM inference and audit logs - operate fully contained within your selected region.In addition, customers with heightened sovereignty requirements (finance, government, defence-adjacent sectors, regulated SaaS) may also opt for a dedicated single-tenant deployment model.
Cognaire Respond runs on a scalable, cloud-native architecture hosted entirely on AWS.The system is built using stateless application services, event-driven AI pipelines, and multi-zone redundancy to provide enterprise-grade reliability and performance.Core infrastructure characteristics:* Auto-scaling compute for AI job processing, ingestion, and vector indexing* Multi-AZ redundancy, so the platform continues operating if an AWS availability zone goes offline* Distributed job execution for large RFP workloads* Isolated subtenant configuration to protect your data* AWS-managed security including encryption in transit and at rest* Fallback and recovery logic for long-running AI jobs* Adoption of AWS Bedrock for secure private LLM inference, never using public endpointsThe result is a resilient, fault-tolerant deployment that scales to support thousands of questions, large corpus structures, and complex multi-stage workflows.
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