Dashdive
AI NativeBreak down cloud costs by feature, team and customer. YC W23.
Break down cloud costs by feature, team and customer. YC W23.
Published Sep 29, 2026
Not publicly documented, but event-level ingestion approaches can create challenges around high cardinality and volume-driven costs, and attribution accuracy can be affected if identifiers are inconsistent.
No public SOC 2, ISO, GDPR/DPA, or related compliance statements were found in accessible vendor materials.
A third-party write-up described a demo flow in which costs were broken down by usage type (for example, data egress), a customer responsible for a cost increase was identified, and a surge was traced to a specific device or object key. This demonstrates the vendor’s attribution model in a demo context, but it does not constitute a verified production deployment analysis.
Most plausible fits:
Decision makers:
End users:
Get a comprehensive analysis of Dashdive including market position, competitive landscape, adoption trends, and peer benchmarks.
Download full report →Need for a mature, broadly reviewed enterprise FinOps suite immediately: If procurement requires vendors with extensive compliance documentation and many third-party reviews, Dashdive’s limited public footprint may present challenges.
Primary need for budgeting, forecasting, RI/Savings Plans optimization, and governance: Mature FinOps suites focus heavily on these workflows; Dashdive’s visible differentiation is detailed attribution.
Immediate coverage required for EC2/EKS/RDS-heavy environments: Dashdive has indicated compute and database service coverage is being added; organizations with central spend in those areas should validate current support.
Requirement for fully self-serve onboarding and instant deployment: Vendor documentation indicates manual provisioning steps and a self-serve option in development.
Need for extensive community validation and many public user reviews: Dashdive’s limited presence on review platforms reduces available external buyer references.
Dashdive has limited presence on major B2B review platforms based on the sources accessible during this research:
Because of limited third-party review coverage, material in this section relies primarily on vendor documentation, acquisition press coverage, and a third-party hands-on write-up.
From vendor documentation (problem framing):
From the Rhombus acquisition announcement: Rhombus indicated Dashdive helped them understand costs on a per-camera and per-customer basis and supported efforts to optimize cloud expenses.
From Dashdive documentation and FAQs: Dashdive states it performs activity attribution at granular levels and supports both agent-based collection and API ingestion of usage events.
Independent customer reviews are scarce. The most concrete limitations documented in vendor materials and independent write-ups include:
What’s described:
What’s missing or not independently verified:
Critical interpretation: This public statement indicates the product was used by a scaled operator prior to acquisition, which provides a practical signal of applicability for similar workloads. Buyers should request a technical case study or reference call for more granular details and verifiable metrics.
Dashdive is a cloud cost observability and unit-economics product designed to attribute multi-tenant cloud spend to business dimensions such as customer, feature, product, and team, and in some cases to endpoint invocation level using observability-style telemetry in addition to cloud billing tags. The product is positioned to move beyond resource-level cost reporting (for example, EC2 instance cost) toward attribution that identifies which customer, feature, or call caused the cost for multi-tenant SaaS and AI workloads.
Dashdive offers two collection modes:
Key supported services/providers (as publicly stated):
Marketing statements from the vendor claim the ability to break down multi-tenant cloud costs by feature. Competitors also provide cost-per-feature or cost-per-customer capabilities, so differentiation is likely to depend on the specific collection and attribution methodology (for example, an agent and network-traffic approach versus tag- or billing-centric approaches).
Dashdive targets:
The product messaging emphasizes visibility similar to application performance monitoring (APM) tools, suggesting relevance to buyers who already invest in observability (OpenTelemetry, tracing, profiling) and want to connect that telemetry to spend.