Ziva and Responsive both address high-volume response work that depends on reusable company knowledge. Responsive publicly positions its AI for RFPs, DDQs and security questionnaires, with trusted content and human verification. Ziva publicly positions source-cited proposal drafting, requirement control, review and document production for RFPs, tenders, DDQs and security questionnaires. A factual comparison tests the declared workflows against the buyer’s own evidence, files, permissions and release controls.
Product categories overlap without being identical. A platform can support the same request type while differing in how content is governed, how evidence is exposed, how users handle exceptions, where data is processed and which operating model it assumes. Vendor speed claims also use different baselines and methods. Comparing headline percentages or feature names can therefore produce false precision.
Treat both vendors as candidates until a controlled evaluation proves fit. Responsive states an 80% faster outcome on its AI page, while Zephior publishes a 91% reference-workflow model and its arithmetic. These figures are not directly comparable without aligned scope, sample and quality criteria. Test the systems on identical work and use accepted output, unsupported claims, reviewer effort, workflow control and contracted deployment as the decision record.
Official sources
What each vendor states publicly
Responsive states that its AI supports RFPs, DDQs and security questionnaires, draws on trusted content and keeps human verification in the process. Its public page also states that teams can respond 80% faster. That is a vendor claim. Buyers should request the underlying definition and verify the outcome in their own workflow.
Zephior states that Ziva supports RFPs, tenders, DDQs and security questionnaires with approved knowledge, source-cited drafting, controlled review and document output. Zephior’s 91% figure is explicitly a reference model comparing a 30-hour manual workflow with 2.7 hours of assisted human oversight. It is not an audited customer average or guarantee.
| Dimension | Ziva public statement | Responsive public statement | Evaluation action |
|---|---|---|---|
| Response scope | RFPs, tenders, DDQs and security questionnaires | RFPs, DDQs and security questionnaires | Weight the actual request mix |
| Knowledge | Approved company knowledge with source-cited drafts | Trusted content is publicly emphasized | Test version, scope, rights and retrieval |
| Human control | Reviewers own verification and release | Human verification is publicly emphasized | Demonstrate block, escalation and approval |
| Speed claim | 91% reference-workflow model with published arithmetic | 80% faster vendor claim | Do not compare until methods align |
| Deployment | European hosting and Swiss-sovereign option published | Confirm the offered configuration with Responsive | Review contract and security package |
Operating fit
Compare how the system handles uncertainty
Common questions with clean sources are useful for orientation but weak for selection. The decisive test is what the platform does with a conflicting policy, an expired answer, restricted evidence, a question that requires legal judgment and a buyer instruction that changes after approval. A dependable response system should make the uncertainty visible and preserve accountable human control.
Ziva should be evaluated closely when visible source support, document-heavy execution and European or Swiss deployment paths are central. Responsive should be evaluated closely when its declared combined RFP and questionnaire operation, trusted-content model and existing ecosystem fit the buyer. In both cases, test the exact contracted edition rather than a generic demonstration environment.
- Require a supported answer, a refusal and an escalation in the test.
- Include restricted and superseded content.
- Measure reviewer behavior, not model fluency.
- Test late changes and released-file traceability.
- Document the exact configuration that passed.
Claims
Do not rank speed percentages without a shared method
A percentage is meaningful only with a defined unit, baseline, assisted scope, sample, quality threshold and collection method. One figure may measure calendar cycle, another active drafting time and another a modeled reference case. Even two measurements of active human time are not comparable if one excludes source preparation or correction.
Ask both vendors for the denominator, sample and definition. Then measure your own baseline and assisted pilot with the same start, end and accepted-quality criteria. Report a distribution rather than selecting the best example. Treat any claim that cannot be reproduced as marketing context, not a financial input.
- Define active time and calendar time separately.
- Include search, review, correction, approval and export.
- Hold accepted quality and response scope constant.
- Report sample size, median and range.
- Use the customer pilot for the business case.
What good looks like
Useful outcomes from Ziva vs Responsive
- Vendor claims are attributed and dated rather than presented as independent findings.
- Headline speed percentages are not compared as if their methodologies were identical.
- The buyer tests source retrieval, answer support, review and release on the same data.
- DDQ and security-questionnaire cases include restricted evidence and accountable approval.
- RFP cases include requirement tracking, collaboration, change and buyer-format export.
- Data location, retention, subprocessors and access controls are evaluated contractually.
- Total effort includes governance, administration, migration and integration.
- The final decision identifies best fit and residual risks rather than a generic winner.
Operating model
How to run the work
- 01
Normalize the requirement
List response families, volumes, languages, file types, portals, users, approvals, knowledge domains, evidence rules, integrations, residency and support needs.
- 02
Create a proof-oriented test corpus
Provide current approved evidence, a superseded policy, restricted content, an unanswered question, a buyer workbook and a long-form document. Use the same corpus in both systems.
- 03
Test ordinary and adverse cases
Run retrieval, drafting, citations or evidence access, assignment, review, escalation, approval, late change and export. Observe what happens when sources conflict or do not support an answer.
- 04
Measure equivalent outcomes
Score final accepted answers, unsupported statements, reviewer corrections, source-check time, missed requirements, export errors, administration and total active human time.
- 05
Confirm the offer in writing
Verify the exact edition, user and usage limits, services, implementation, integrations, security, data residency, support, price, renewal and exit terms.
Evaluation
Questions that change the decision
- Is the primary need RFP proposal production, trust-center questionnaires or a combined response operation?
- Must reviewers see the precise source used for each drafted statement?
- How are approved answers scoped by product, region, customer, policy version and confidentiality?
- Which questions must be blocked or escalated when evidence is missing?
- What audit record is required for edits, approvals and released files?
- Which European or Swiss deployment requirement applies to the contracted service?
- What implementation and knowledge-governance capacity exists internally?
- How will the business compare quality and effort after rollout?
Failure modes
Where teams lose control
Vendor-reported speed claims may use different units, baselines and samples.
Trusted content can still be obsolete, mis-scoped or inaccessible to the right reviewer.
Answer generation can create confidence without adequate evidence.
Security-questionnaire automation can reuse customer-specific commitments in the wrong context.
Workflow depth can add administration if ownership and states are not simplified.
Export fidelity can fail on unusual workbooks or portal constraints.
Packaging and integration costs can materially change total cost.
Public product information can change after the stated review date.
Measurement
Measure the finished job
Measure the completed workflow, including review effort and exceptions. Output volume on its own is not evidence of a better process.
- accepted response rate on the common test set
- unsupported or mis-scoped statements
- reviewer time and substantive corrections
- source retrieval and verification time
- missed requirements and approval exceptions
- buyer-file import and export defects
- knowledge curation and access administration
- active human effort and calendar cycle
- implementation and integration effort
- contracted total cost and exit effort
Questions
Common questions
Is Ziva an alternative to Responsive?
It can be evaluated as an alternative for RFP, tender, DDQ and security-questionnaire work. The correct choice depends on the tested workflow, evidence controls, integrations, deployment, commercial terms and transition effort.
Can the 91% and 80% claims be compared directly?
No. They are vendor claims with different public descriptions. Align baseline, scope, sample and quality criteria, then measure both products on the same customer workload.
Which platform is better for security questionnaires?
Both publicly address security-questionnaire work. Test restricted evidence, policy versions, unsupported questions, SME approval, customer-specific commitments and final export in the offered edition.
What is the most important evaluation metric?
Accepted final output with evidence and total human effort is more useful than draft speed alone. Track unsupported statements, substantive rewrites, source-check time and release defects.
When was this comparison reviewed?
The official sources on this page were reviewed on 22 August 2026. Verify current capabilities and terms with both vendors.
Sources
Primary references
- Responsive AI Responsive
- Ziva proposal software Zephior
- Ziva performance methodology Zephior
- Zephior security Zephior
About the author
Tony Kim
Tony writes about applied AI, dependable product engineering and the systems that turn complex response work into controlled delivery.
Ziva
Proposal software for source-grounded RFP, RFI, DDQ and questionnaire response work.
Bid, proposal, presales, security and compliance teams. Start with the workflow, constraints and evidence you already have.
