Most low-code vendor evaluations come down to whoever runs the most polished demo. That is a bad way to spend several years of the IT budget. The platforms in the shortlist all look similar in a 45-minute pitch. The differences show up two years later, when the platform has to handle real workloads, real governance demands, and real change requests.
Gartner expects 75 percent of new enterprise applications to be built on low-code platforms by 2026. The market has grown fast enough that more than a dozen vendors now claim enterprise-grade capabilities. A structured scorecard is the only practical way to compare them.
Standard RFP templates focus on feature checklists. Every modern low-code vendor will check most boxes on every list. Drag-and-drop builder, prebuilt connectors, mobile support, role-based access, AI features. The feature gap between leading platforms has narrowed to near zero on paper.
The real differences sit underneath the features. Governance posture, pricing model, integration depth, vendor roadmap, and support for the way enterprise IT actually operates. A useful scorecard pulls those differences out into the open and forces the vendor to answer them in writing.
The 12 questions below are organized across four categories that capture where platforms actually diverge. Score each vendor from one to five against your own weighting, and the answer usually becomes clear before the final round of demos.
Every vendor will say their platform handles complex logic. Ask for a specific example: a multi-step approval workflow with conditional branching, parallel paths, exception handling, and integration with two external systems. If the answer requires custom code or a developer-only environment, the platform is closer to a developer tool than a true low-code platform.
Ask for a list of prebuilt connectors that match your specific stack. Generic API support is not enough. If the vendor needs to build a custom connector for your ERP, expect a multi-month project before the platform delivers value.
A platform optimized only for developers will not unlock business users. A platform optimized only for business users will not scale to complex applications. The platforms that win at the enterprise level support both audiences in the same environment, with appropriate guardrails for each.
Ask about the largest production deployment running on the platform today. Number of users, number of apps, transactions per day. If the vendor cannot point to a customer running at the scale you need, your deployment becomes their reference customer.
Ask for the average, not the best case. Gartner reports that only 48 percent of digital initiatives meet or exceed business outcome targets. Time to first production app is one of the strongest predictors of whether the initiative ends up in that 48 percent.
The strongest argument for low-code is that it shifts work from a scarce resource, engineering capacity, to a more available resource, business users with the right training. Ask what percentage of applications are typically built by business users on the platform after 12 months.
Per-user, per-app, per-workflow, per-execution. Each model creates different incentives. Per-user pricing penalizes broad rollout. Per-app pricing penalizes departments building many small apps. Per-execution pricing creates unpredictable costs for high-volume workflows. Get a three-year cost projection based on your specific usage pattern, not the vendor's standard pricing sheet.
Ask about response SLAs, dedicated customer success resources, and access to engineering for escalations. Some vendors restrict premium support to the highest pricing tier. Others bundle it with all enterprise contracts.
Ask for current certifications: SOC 2 Type II, ISO 27001, GDPR readiness, HIPAA if relevant, FedRAMP if applicable. Gartner expects more than 60 percent of AI projects to fail by 2026 in organizations that do not align their data and governance practices with enterprise use cases. Compliance posture is part of that alignment, not a separate conversation.
Some vendors push major updates that break custom configurations and require rework. Others maintain backward compatibility across major versions. Ask for the upgrade history of the past three years and check how often customers have had to rebuild work after a release.
AI capabilities have moved from differentiator to baseline expectation. The question now is what the AI actually does. Code generation that produces opaque output is different from AI that generates structured, auditable application blueprints. Ask the vendor to explain their AI approach in detail. Their answer reveals whether the platform is built for fast demos or for applications that need to survive five years.
Industry, region, company size, and use case all affect whether a vendor's experience translates to your situation. Ask for three references that match at least three of those four criteria. If the vendor cannot provide them, the platform may be a fit somewhere, but not necessarily a fit for you.
Each question gets a score from one to five. Five means the vendor demonstrated a clear, specific answer backed by evidence. One means the answer was vague, evasive, or absent. Anything in the middle is a partial answer that needs follow-up.
The weighting matters more than the scoring. A platform with strong technical capability but weak compliance posture is wrong for a regulated industry, but right for an internal IT use case at a less regulated company. Set the weights based on which dimensions matter most for your specific portfolio of applications, and let the math do its job.
Total scores across vendors usually fall within a narrow range. The pattern of strengths and weaknesses matters more than the headline number. A vendor that scores high on integration and governance but low on time-to-value is a different bet than one that scores high on time-to-value but low on enterprise scale.
Kissflow is built for the enterprise low-code conversation, not the developer-tool conversation. The platform supports both business users and IT teams in the same environment, with audit trails, role-based access, and version control turned on by default rather than added as a premium tier.
AI in Kissflow generates application blueprints, not code. A blueprint is a structured description of what the application does: forms, fields, approval logic, integrations. Business users and IT teams can both read it, change it, and govern it. This is a deliberate architectural choice. Code generation is fast on day one and increasingly difficult to maintain by day 90. Blueprints stay readable, auditable, and changeable as the business evolves.
On the commercial side, Kissflow uses predictable per-user pricing rather than per-app or per-execution models. That makes the three-year cost projection a straightforward calculation, not a guess. On compliance, the platform ships with SOC 2 Type II, GDPR readiness, and the access controls regulated industries need. Customers in financial services, manufacturing, healthcare, and higher education run production applications on Kissflow at scale.
Time to first production application for a workload that matches your real use case. Demos can show what is possible. Time to first production application shows what is realistic when your team owns the build.
Ask the vendor to explain specifically what their AI generates and how that output is governed over time. AI that generates raw code creates a maintenance problem. AI that generates structured application blueprints stays readable, auditable, and changeable by both business users and IT.
They are a useful starting point but not a decision tool. The Magic Quadrant evaluates vendors on broad criteria. Your decision needs to weight those criteria against your specific applications, integration stack, compliance requirements, and budget model.
Between six and ten weeks for an enterprise decision. That includes shortlisting, structured demos against the same use case, reference calls, a proof of concept on at least one platform, and final commercial negotiation.
Integration development for systems without prebuilt connectors, premium support tiers, additional licensing for advanced features, training and enablement costs, and the cost of rebuilding applications after major platform upgrades.
Power Platform is worth evaluating, but with eyes open. The per-user licensing complexity, the dependency on the broader Microsoft ecosystem, and the governance challenges at enterprise scale all need to be costed into the comparison rather than assumed away because of existing Microsoft commitments.
Ask for the largest production deployment running on the platform, the transactions per day at peak, and the number of business users active. If the vendor cannot answer those questions specifically, the platform may not have proven scale at the level you need.