Small company, 50 employees. Automated 30 processes in 6 months. Saved 4,000 hours/year (2.5 FTE equivalent). Lesson: the hardest part wasn't the platform — it was deciding which processes to automate first.
Small company, 50 employees. Automated 30 processes in 6 months. Saved 4,000 hours/year (2.5 FTE equivalent). Lesson: the hardest part wasn't the platform — it was deciding which processes to automate first.
Small company, 50 employees. Automated 30 processes in 6 months. Saved 4,000 hours/year (2.5 FTE equivalent). Lesson: the hardest part wasn't the platform — it was deciding which processes to automate first.
Mid-size company, 200 employees, 300 Zaps. Migrated to new platform: 3 months planning, 6 weeks execution, 2 weeks dual-running. Result: 40% cost reduction, but $45,000 migration labor. Lesson: plan for 2x estimated time and 1.5x estimated cost.
Large company, 5,000+ employees. Department pilot → enterprise-wide in 12 months. Enablers: executive sponsor, Center of Excellence, governance, training. Barriers: IT security review (4 months), procurement (3 months), change management. Result: 500+ automations, $2M/year savings, 15 FTE equivalent. Lesson: enterprise adoption is change management, not technology.
Company used Platform A for 2 years, switched to Platform B. Why: unsustainable pricing, lagging AI, degraded support post-acquisition. Pivot cost: $120,000 labor, 4 months disruption. Lesson: evaluate on 3-year trajectory, not current feature list.
Company chose self-hosted for "free" and "control." Reality: $15,000/year infrastructure, 0.5 FTE maintenance, 2 major outages in 18 months. 3-year TCO: $75,000 vs $12,000 managed. Lesson: "free" software costs in infrastructure, labor, and risk.
Company adopted agent-native platform. Month 1: "this feels different." Month 3: agents handle 80% of routine automation independently. Month 6: team spends more time on strategy than building. Result: 3x automation output vs previous workflow platform. Lesson: the paradigm shift from "build automations" to "describe outcomes" is the real value.
Healthcare company needed HIPAA-compliant automation. 3 of 5 platforms couldn't sign a BAA. 1 could but had no healthcare integrations. 1 could but was 5x budget. Result: compliant automation but 300+ hours custom dev. Lesson: in regulated industries, compliance filters eliminate 80% of platforms before features are discussed.
Company discovered 47 different automation tools across departments. No governance, duplicated automations, security risks. Centralized on one platform. Result: 60% cost reduction, improved security. But: 18-month consolidation faced department resistance. Lesson: consolidation is organizational change, not IT.
Company expected labor savings. Actual ROI: 40% labor (expected), 30% error reduction (unexpected), 20% speed improvement (unexpected), 10% employee satisfaction (unexpected). Total: 3x initial estimate. Lesson: measure everything — biggest ROI often comes from unanticipated benefits.
Company evaluated platforms, ran PoC, decided not to proceed. Why: processes weren't standardized enough. Spent 12 months standardizing, then re-evaluated. Second PoC succeeded. Lesson: sometimes "not yet" is the right decision — automation reveals process problems that should be fixed first.
Every case study needs: Company Profile (industry, size, maturity), Challenge (problem to solve), Evaluation (platforms considered, why chosen), Implementation (timeline, resources, what went wrong/right), Results (quantitative: hours, cost, errors + qualitative: satisfaction, improvement), Lessons Learned (what they'd do differently, advice for others).
A great library has: Breadth (across industries, sizes, use cases), Depth (detailed metrics, not just "saved time"), Authenticity (real companies, real names, real quotes), Recency (last 18 months), Searchability (filterable by industry, size, use case). The library is the platform's proof. Without it: claims. With it: evidence.
Features get evaluated. Case studies get bought. A platform with great features but sparse case studies loses to a competitor with adequate features and 47 case studies — including 3 from the buyer's industry, size, and use case. Gobii must close the case study gap to convert enterprise buyers who need proof, not promises.
This analysis is based on publicly available documentation, community forums (Reddit, Discord, GitHub), vendor-published case studies, security compliance reports, and hands-on testing by the gobii.reviews editorial team. All claims are sourced and verified. We do not accept payment for inclusion or ranking. See our full methodology and editorial standards.
Last updated: June 30, 2026. Published by the gobii.reviews Editorial Team.