Driftly
AI NativeScheduling automation for home health agencies, reducing clinician travel time by 30-50%
Est 2024|Raised $500K
Published Sep 19, 2026
These items are vendor-reported. There is insufficient independent public evidence in the sources reviewed in this run to confirm consistent achievement of these benefits across customer deployments.
Conclusion: As of March 2026, Driftly appears to be early-stage and lacks broad coverage on major B2B review platforms (or it may be difficult to find due to naming collisions).
A launch post includes specific performance claims attributed to the vendor, including numerical impacts on productivity, drive time, and revenue. These items are vendor-reported and were not accompanied by methodology or independent validation in the public materials located during this run. Buyers should request supporting pilot data, definitions, sample sizes, and methodology.
Given Driftly's early-stage profile and focus on routing/scheduling optimization, an initial practical fit is likely mid-sized agencies (e.g., dozens to several hundred field clinicians) where scheduling complexity is sufficient to justify optimization and operational decision-making processes are not overly bureaucratic.
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Download full report →The organization requires documented compliance artifacts (SOC 2, HIPAA/BAA readiness) immediately and cannot accept an "in-progress" posture. The vendor site pages reviewed do not document these certifications publicly.
The organization requires a full home health EHR replacement. Driftly is positioned as an optimization and scheduling layer rather than a complete EHR.
The agency has minimal scheduling complexity. Small or low-volume operations may not see sufficient ROI relative to process improvements.
The current EHR is the system of record for schedules and will not support robust integration or write-back. The vendor's read/write claims should be validated in technical discovery.
The procurement process requires abundant third-party reviews and references. The vendor appears early-stage with limited public review coverage.
Critical evaluation: Without baseline distributions (e.g., drive-time distributions), territory density context, pilot methodology, and other controls, these metrics should be treated as vendor-reported and not decision-grade evidence.
Suitable when:
Deal disqualifiers:
Driftly is described as a scheduling, dispatching, and route-optimization layer for home health agencies that uses machine learning models to support clinician-to-patient assignment. The vendor describes goals such as matching clinicians to patients, reducing drive time, and improving utilization. The vendor also links these operational outcomes to potential improvements in quality metrics such as OASIS outcomes and HHVBP performance.
The vendor materials highlight: