Written by: Nimesh Chakravarthi, Co-founder & CTO, Struct
Key Takeaways for Teams Evaluating Resolve AI
- Resolve AI’s verified 2026 customers include Coinbase, Zscaler, DoorDash, MongoDB, Salesforce, and MSCI. These are primarily large enterprises with complex SRE needs.
- Enterprise customers report strong results, including Coinbase’s 73% faster root cause identification and Zscaler’s large-scale alert handling with fewer engineer pages.
- Resolve AI fits enterprises that can support lengthy sales cycles and weeks-long setups. This structure makes the platform a poor fit for most startups.
- Struct gives Seed to Series C teams a faster path, with 10-minute setup, 80% triage reduction, and a Slack-native interface that fits existing workflows.
- Teams that want to cut manual triage by 80% can book a Struct demo and see the impact on their on-call load.
Enterprise Customers Using Resolve AI in 2026 (Proof & Outcomes)
Resolve AI’s public customer list centers on large enterprises with demanding reliability and incident response requirements.
1. Coinbase
Coinbase trained Resolve AI on past incidents using Kubernetes and Datadog, achieving 73% faster time to root cause. Their implementation handles complex scenarios, such as tracing poorly tuned load tests through dependency graphs in minutes. It also identifies out-of-memory errors in sidecars within 12 minutes while linking cascading failures.
2. Zscaler
Zscaler uses Resolve AI for autonomous alert investigations across 150,000 alerts and 120 incidents monthly. The team targets a reduction of mid-severity incident resolution from 1 hour to 15 minutes, with at least 30% fewer engineer pages required per incident.
3. DoorDash
DoorDash relies on Resolve AI to manage production environments and deliver more reliable customer experiences. The company reports faster movement in production, although specific performance metrics remain undisclosed.
4. MongoDB
MongoDB appears among Resolve AI’s enterprise customers that help engineering teams deliver reliable experiences. Public details about MongoDB’s exact implementation are not available.
5. Salesforce
Salesforce uses Resolve AI’s platform to manage production environments. The company has not shared specific use cases or quantified impacts.
6. MSCI
MSCI is confirmed as a Resolve AI customer for production environment management. Public information about their specific implementation remains limited.
| Company | Use Case | Impact | Source |
|---|---|---|---|
| Coinbase | Kubernetes/Datadog incidents | 73% faster root cause | Resolve.ai |
| Zscaler | Autonomous alerts (150k/mo) | 30% fewer engineers/incident | Resolve.ai |
| DoorDash | Production management | Faster production velocity | Resolve.ai |
| MongoDB | Reliability engineering | Improved customer experience | Resolve.ai |
These enterprise deployments involve extensive sales processes and complex setup procedures. Resolve AI therefore suits large-scale organizations with dedicated SRE teams and longer implementation timelines.
Resolve AI vs. Struct, Grafana Cloud, and Dynatrace
Resolve AI focuses on deep enterprise capabilities, while several alternatives focus on speed, simplicity, and startup readiness. The comparison below highlights a consistent tradeoff: enterprise-grade depth often comes with enterprise-level complexity, while startup-focused tools prioritize fast deployment and lighter workflows.
| Feature | Resolve AI | Struct | Grafana Cloud |
|---|---|---|---|
| Setup Time | Weeks/demos | 10 minutes | Days |
| Triage Reduction | 72-73% (select) | 80% | ~60% |
| Best For | Enterprise | Startups | Mid-market |
| Compliance | Enterprise-grade | SOC2/HIPAA | Varies |
Struct stands out for fast-growing teams with its Slack-native interface and proactive investigation capabilities. Customers such as FERMAT and Arcana report a verified 80% triage reduction. Struct avoids the heavy enterprise sales model and deploys in 10 minutes, which delivers immediate value for Seed to Series C companies.
Grafana Cloud offers strong dashboard capabilities and broad support for open standards. Dynatrace provides enterprise-grade causal AI with premium pricing that often limits adoption by smaller teams.
Teams that prioritize speed and simplicity can see how Struct’s 10-minute setup compares to enterprise alternatives before committing to a heavier platform.
Key Insights from Real-World Resolve AI Usage
Verified Resolve AI implementations show that enterprises can achieve meaningful MTTR improvements. Coinbase’s 73% faster root cause identification illustrates the upper bound of documented impact. These gains, however, depend on substantial upfront investment in training data, integrations, and process changes.
The gap between marketing claims and accessible proof points creates skepticism among SRE practitioners. Reddit discussions often question the limited number of detailed case studies beyond a small set of enterprise logos. Junior engineers also report difficulty during incidents when they lack clear context and practical examples.
Industry data shows typical manual triage consuming 30 to 45 minutes per alert, which creates unsustainable workloads for on-call engineers. This pain point helps explain why Resolve AI’s MTTR reductions attract large enterprises. The complex setup process required to reach those results, however, excludes fast-moving startups that need immediate relief without months of implementation work.
Struct addresses this gap with instant deployment and quick time to value. Teams can reach similar triage reductions without the heavy complexity that enterprise platforms require. The platform’s composable architecture supports customization while preserving the simplicity that lean engineering teams depend on.
Teams that want to reclaim product velocity can book a demo to see how Struct reclaims their engineering focus and reduces time spent on manual incident response.
Frequently Asked Questions
What companies use Resolve AI?
Verified Resolve AI customers include Coinbase, Zscaler, DoorDash, MongoDB, Salesforce, and MSCI. These accounts appear in the enterprise customer profiles above, where each logo includes the available public details.
Which companies are using Resolve AI in 2026?
The confirmed 2026 customer list matches the core enterprise clients announced during Resolve AI’s Series A funding round. The company has raised $125 million and reached a $1 billion valuation, yet public disclosure of additional customers remains limited beyond the original six enterprise accounts.
How does Resolve AI compare to competitors?
Resolve AI performs well in enterprise environments with complex requirements but requires lengthy setup processes. Alternatives such as Struct offer faster deployment, with 10-minute setup instead of weeks, higher triage reduction at 80 percent, and better alignment with startup needs. Grafana Cloud provides strong support for open standards, and Dynatrace focuses on premium enterprise features at a higher cost.
Is Resolve AI worth it for startups?
Resolve AI’s enterprise focus makes it impractical for most startups because of complex sales processes, long implementation timelines, and heavy resource requirements. Struct delivers stronger value for Seed to Series C companies, with 10-minute setup, 80 percent triage reduction, and SOC2 and HIPAA compliance without enterprise-level overhead.
What is the typical setup time for these platforms?
Resolve AI often requires weeks or months for full deployment, including dedicated sales engagement and custom integration work. Struct deploys in about 10 minutes through simple authentication with existing tools such as Slack, GitHub, and Datadog. Grafana Cloud typically takes several days for configuration and dashboard setup.
Conclusion: Choosing the Right Incident Automation Platform
Resolve AI serves enterprise customers such as Coinbase and Zscaler with proven MTTR improvements, yet the platform’s complexity limits accessibility for fast-moving startups. Teams that need immediate triage reduction should evaluate Struct’s 10-minute deployment and 80 percent efficiency gains as a more practical option.
Stop burning engineering cycles on manual incident response. Book a demo to see how Struct transforms your team’s reliability operations and frees engineers to focus on product work.
