# RunLLM vs Struct

RunLLM records 182 monthly visits with -90.6% month-over-month growth and Free Trial, Contact for Pricing pricing. Struct records 74 monthly visits with -95.2% growth and Freemium, Free pricing.

| Metric | [RunLLM](https://openaitools.app/tool/runllm) | [Struct](https://openaitools.app/tool/struct) |
| :--- | :--- | :--- |
| Website URL | https://www.runllm.com | https://struct.ai |
| Categories | AI Agent, AI Customer Service, AI Assistant, AI Code Assistant | AI Agent, AI Developer Tools, AI Assistant, AI Code Assistant |
| Pricing Model | Free Trial, Contact for Pricing | Freemium, Free |
| Monthly Visits | 182 | 74 |
| MoM Growth Rate | -90.6% | -95.2% |
| Primary Market | Global | United States |
| Direct Visits | 71 | 29 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## RunLLM

RunLLM, now operating under the Herald brand, has evolved from an enterprise technical-support assistant into what it calls an AI SRE: an agent that catches production issues before engineers are even paged. The pitch is that traditional observability is broken — you have to instrument every data stream, tune alert thresholds, and write runbooks for each failure mode, and anything nobody documented stays invisible.

Herald takes a different approach. Before any alerts fire, it builds a context graph spanning your observability, codebase, CI/CD, documentation, and dependencies, so it learns what normal looks like. It then builds a custom anomaly detection model for each data stream — no thresholds to set — and surfaces validated signals before customers notice. When something looks wrong, the agent evaluates multiple hypotheses simultaneously against the right data sources and hands engineers a root-cause analysis in minutes, no runbook required.

The company reports 100% RCA accuracy on known issues and over 70% on novel incidents for one of the world's biggest B2B2C platforms, and notes that the agent learns from every investigation so it never makes the same mistake twice. Herald was founded by PhDs and professors from UC Berkeley's RISELab, combining expertise in AI, LLMs, data systems, and scalable infrastructure.

**Pricing & Plans:** Free trial with demos available; enterprise pricing is quoted on request via sales contact. Check the site's pricing and demo pages for current details.

- **Context-aware learning:** Herald builds a context graph across observability, codebase, CI/CD, docs, and dependencies before alerts fire, so it understands what normal looks like.
- **Predictive detection:** No thresholds to tune: Herald builds a custom anomaly detection model for each data stream and surfaces validated issues before customers notice.
- **Automated investigation:** The agent evaluates multiple hypotheses at once against the right data sources and delivers root-cause analyses in minutes without runbooks.
- **Grounded in production:** 100% RCA accuracy on known issues and 70%+ on novel incidents, learning from every investigation so it never repeats a mistake.
- **Fast onboarding:** Scans your codebase, finds the tools you use, and configures itself in minutes, adapting quickly to your stack.

**Strengths:** Detects and investigates issues before alerts fire; No thresholds or runbooks to author and maintain; Correlates signals across code, infra, and telemetry; Built by UC Berkeley RISELab researchers

[Profile (Markdown)](https://openaitools.app/tool/runllm.md)

## Struct

Struct positions itself as the missing piece of a modern software factory: an AI production engineer that catches and fixes production issues before customers notice. Rather than asking teams to hand-write monitoring, Struct reads every pull request and creates the monitors, metrics and thresholds needed to verify that specific change in production. No code changes are required, and after deployment it baselines alert thresholds automatically so the team can keep shipping without tuning dashboards.

The second half of the product is triage and remediation. Every alert is assessed, noise is dismissed or automatically tuned as production drifts, and only genuine issues are escalated — each one arriving with an owner, an impact analysis and a root cause traced to a file and line. When Struct is confident, it opens a fix PR itself, or it can hand the job to your own coding agent or software factory, which keeps engineers in the review-and-merge role instead of the firefighting role. Incident channels are also covered: Struct auto-joins, co-investigates as new evidence appears, follows up on leads and keeps the investigation updated.

Struct Overwatch adds a proactive layer, periodically scanning the whole system to find cross-service issues behind clusters of alerts — or silent problems that have not alerted at all. The company reports SOC 2 Type II and HIPAA compliance, encrypted and logically isolated data, and no use of customer data for model training. Pricing is Pro at $200 per month, which includes 50 PR scans, 25 investigations and fixes, 250 managed monitors, four incidents, daily Overwatch and up to 10 users with Slack support, plus a custom Enterprise tier with volume discounts, hourly Overwatch, RBAC and SSO/SAML.

**Pricing & Plans:** Free trial to start, then Pro at $200/month covering 50 PR scans, 25 investigations and fixes, 250 managed monitors, 4 incidents, daily Overwatch, up to 10 users and Slack support. A custom Enterprise tier adds volume discounts, hourly Overwatch, custom integrations, RBAC, SSO/SAML, unlimited users and a dedicated account manager. Annual discounts and non-expiring top-ups are available.

- **Monitors for every PR:** Struct reads each pull request and generates the monitors and metrics needed to verify that change in production, with no code changes required, then baselines alert thresholds automatically after deploy.
- **Alert triage without the noise:** Every production alert is triaged automatically. Irrelevant ones are pruned, flappy ones are tuned as prod changes, and only real issues are escalated — each arriving with an owner, impact analysis and root cause.
- **Hands-free fixes:** When Struct is confident, it can open a fix PR on its own. You can also connect your own coding agent or software factory and let Struct dispatch and coordinate the remediation.
- **On-call intelligence that improves:** Struct accumulates context from your repositories, past incidents, alerts, fixes and team feedback, so guidance given once — such as never holding a database connection across a sleep — is remembered and applied to future PRs.
- **Incident investigation and Overwatch:** Beyond reacting to alerts, Struct Overwatch periodically scans your entire system to catch production-spanning issues behind multiple alerts, or emerging problems that have not triggered any alert yet.

**Strengths:** Automatically creates monitors and metrics per pull request with no code changes or manual dashboard work; Triages and tunes alerts continuously so engineers only see issues with real impact; Root causes arrive with owner, impact analysis and a specific file and line reference; Can open fix PRs autonomously or delegate to your own coding agent

**Limitations:** Pro plan starts at $200/month, which is significant for small teams or solo developers; Autonomous fix PRs require connecting a coding agent such as Devin, so full hands-free remediation depends on a second tool; Setup is CLI/app based and integrations, while broad, need to be wired into your existing observability and chat stacks first; The product is aimed squarely at engineering and DevOps teams; non-technical users will find little to do here

[Profile (Markdown)](https://openaitools.app/tool/struct.md)

## Frequently Asked Questions

### How do RunLLM and Struct compare in monthly traffic?

RunLLM has 182 monthly visits, while Struct has 74. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

RunLLM has a month-over-month growth rate of -90.6%; Struct has -95.2%.

### How does pricing compare?

RunLLM: Free Trial, Contact for Pricing. Free trial with demos available; enterprise pricing is quoted on request via sales contact. Check the site's pricing and demo pages for current details. Struct: Freemium, Free. Free trial to start, then Pro at $200/month covering 50 PR scans, 25 investigations and fixes, 250 managed monitors, 4 incidents, daily Overwatch, up to 10 users and Slack support. A custom Enterprise tier adds volume discounts, hourly Overwatch, custom integrations, RBAC, SSO/SAML, unlimited users and a dedicated account manager. Annual discounts and non-expiring top-ups are available.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Cursor](https://openaitools.app/tool/cursor) | 23,297,751 | +8.4% | Freemium | The AI coding agent for building ambitious software | [.md](https://openaitools.app/tool/cursor.md) |
| 2 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Google's agent-first development platform for building and shipping software with AI agents | [.md](https://openaitools.app/tool/google-antigravity.md) |
| 3 | [Replit](https://openaitools.app/tool/replit) | 10,016,437 | -7.7% | Freemium, Paid | Describe your idea and Replit builds a working app in minutes | [.md](https://openaitools.app/tool/replit.md) |
| 4 | [Kiro](https://openaitools.app/tool/kiro) | 3,330,476 | +4.6% | Freemium | A spec-driven AI IDE and agent platform that plans, builds, reviews, and verifies real engineering work. | [.md](https://openaitools.app/tool/kiro.md) |
| 5 | [Devin](https://openaitools.app/tool/devin) | 2,549,346 | +1% | Paid | Cognition's autonomous software engineer that ships real pull requests | [.md](https://openaitools.app/tool/devin.md) |
| 6 | [Command Code](https://openaitools.app/tool/command-code) | 2,358,177 | -12.1% | Freemium, Contact for Pricing | The coding agent that learns your coding taste | [.md](https://openaitools.app/tool/command-code.md) |
| 7 | [Orca](https://openaitools.app/tool/orca) | 1,025,891 | +1% | Free, Open Source, Enterprise on request | Run many coding agents in parallel, each in its own worktree | [.md](https://openaitools.app/tool/orca.md) |
| 8 | [KaneAI](https://openaitools.app/tool/kaneai) | 901,340 | +13.2% | Freemium, Paid, Contact for Pricing | GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language | [.md](https://openaitools.app/tool/kaneai.md) |
| 9 | [Warp](https://openaitools.app/tool/warp-ai) | 657,372 | -9.3% | Freemium, Contact for Pricing | AI-powered terminal and agentic software factory for development teams | [.md](https://openaitools.app/tool/warp-ai.md) |
| 10 | [Augment Code](https://openaitools.app/tool/augment-code) | 326,215 | +24.1% | Freemium, Free Trial, Contact for Pricing | Agent orchestration platform for your whole software development lifecycle | [.md](https://openaitools.app/tool/augment-code.md) |

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Source: https://openaitools.app/compare/runllm-vs-struct

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