Top 10 AI SOC Vendors in 2026: A Practitioner's Comparison

Q1. What Are the Top 10 AI SOC Vendors in 2026?

Ranked by composite score across five weighted criteria (full methodology in Q3):

1. BlinkOps: Best for teams that want an agentic platform where AI SOC is one of many solutions they can use or build
2. Torq: For teams that want to build it themselves on a simplified, low-code UI
3. Swimlane: For MSSPs that want to invest in heavy engineering of the platform
4. Exaforce: For cloud and SaaS-heavy environments wanting multi-model investigation
5. Intezer: Great for forensic-grade investigation of every alert
6. Prophet Security: For teams that want investigation depth and visible reasoning
7. Dropzone AI: Good for fast, low-friction autonomous triage on top of an existing stack
8. CrowdStrike: Best for organizations already standardized on Falcon
9. Google SecOps: Good for teams centralizing on Chronicle and Google Cloud
10. Radiant Security: Best for mid-market teams drowning in alert noise

These ten are not interchangeable. They sit in three categories that solve three different problems: SOAR platforms that pivoted to agentic AI, pure-play AI SOC analysts, and the SIEM and endpoint giants bundling AI SOC into their suites. Category matters as much as rank, and the order here reflects fit for a vendor-neutral, agentic-first SOC, which is the buyer this guide is written for. The methodology makes that explicit.

Q2. How Do the Top 10 AI SOC Vendors Compare at a Glance?

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Star ratings map to the composite scores in Q3. Deployment model shows whether a platform ships ready to use (plug and play), can be tailored to your environment (customizable), or expects you to build the SOC solution yourself (build it yourself). BlinkOps is the only entry that offers all three on one platform. An agent builder, the ability to create, modify, and deploy custom AI agents per alert type and environment rather than taking vendor-locked agents as-is, is a key differentiator for teams that want control over their automation.

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Q3. How Did We Score These Vendors?

Every "best of" list has a bias baked into its scoring. The honest move is to show the bias, not hide it. Here's ours.

We scored all ten platforms out of 100 across five weighted criteria, then mapped the score to a star band. We weight the full investigation-to-response loop and vendor neutrality most heavily, because our thesis is simple: a verdict you can't act on isn't a finished job, and a capable AI that only works inside one vendor's ecosystem is worth less to a multi-vendor SOC than a slightly narrower one that runs across your whole stack. That weighting is why the SIEM-bundled platforms, capable as they are, rank below the vendor-neutral options here. It also favors platforms over point tools. We're telling you that openly, and we're telling you how to change it.

If you've standardized on one ecosystem (all-in on Falcon, or all-in on Google Cloud), raise the weight on investigation depth, drop vendor neutrality, and the SIEM-bundled platforms climb. That's the right rubric for that buyer. If your only problem is L1 triage relief, raise criteria 1 and 5 and drop 3 and 4, and the pure-plays climb further. We'd point you there.

The Five Weighted Criteria

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Star Rating Bands

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Composite Scores (as of June 2026)

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Scores reflect what is in production as of June 2026, not roadmap, and are derived from vendor documentation, public capability disclosures, and hands-on category analysis. The SIEM-bundled platforms land at the low end of the four-star band because the rubric weights vendor neutrality heavily; on an ecosystem-standardized rubric they rank higher, as noted above.

Q4. How Do You Actually Categorize AI SOC Vendors?

"AI SOC" is the most overloaded term in security right now. One vendor means an LLM that summarizes alerts on top of your SIEM. Another means autonomous agents that triage, investigate, and respond across your whole stack. Lumping them into one list is how buyers end up comparing a feature against a platform.

The lens that cuts through it: where does the product sit in the SOC workflow, and how much of that workflow does it actually own?

SOAR turned AI SOC. Torq, Swimlane, and D3 started as automation platforms and added agentic AI,  AI agents that reason, decide, and act within guardrails rather than following a fixed script, on mature workflow engines. They own response well. The question is how real their agent layer is versus how much you still build yourself.  (See: How to Replace SOAR with an Agentic SOC Platform.)

Pure-play AI SOC. Dropzone, Prophet, Exaforce, and Radiant were built AI-native around one job: investigate the alert and return a verdict. They're fast to deploy and strong at triage. The question is what happens after the verdict, because most of them stop there.

SIEM and endpoint vendors with AI SOC. CrowdStrike and Google SecOps bundle AI SOC into a platform you may already own. They have the data and the context. The question is whether the AI works when you don't send everything to their platform, and whether their automation is real or a checkbox.

Agentic platforms. BlinkOps sits in a fourth category: an Agentic Security Operations Platform where AI SOC is one solution among many, built on the same foundation as threat hunting, threat intel, and malware analysis solutions.

Picture the SOC workflow as a left-to-right pipeline: ingestion and detection engineering on the left, enrichment and triage and investigation in the middle, response and remediation and the feedback loop on the right. Pure-plays own the middle. SOAR vendors own the right. SIEM vendors own the left. Almost nobody owns the whole line, and that gap is the most important thing to understand before you buy.

1. BlinkOps: Best for an Agentic Platform Where AI SOC Is One of Many Solutions

What it is. An Agentic Security Operations Platform. AI SOC is one solution on it, not the whole product. The same platform ships pre-built solutions for threat hunting, threat intelligence, and malware analysis, and lets you build custom solutions on the same foundation. Under the hood it runs Agentic SOC and Agentic SOAR, with case management built in, 500+ pre-built agents  (as of June 2026), and 30,000+ governed actions across 400+ vendors.

Where it wins. It matches the pure-plays on speed, with plug-and-play Agentic SOC and initial triage (intent, possible impact, severity) in under 60 seconds, then goes further than they can. A two-phase investigation runs fast triage in phase one and in-depth, governed response in phase two, customized to how your team actually works. Most pure-plays only do phase one and hand off.It gives you a real agent builder, the ability to create and deploy custom AI agents from playbooks to micro-agents per alert type, per environment, per detection, rather than vendor-locked monoliths or agent nodes trapped inside a workflow.It closes the response loop on one platform across 30,000+ actions, not a fixed menu of basic containment and not a handoff to your existing SOAR. The agentic-plus-deterministic architecture, where deterministic workflows (fixed, rule-based execution paths) enforce guardrails while agents reason flexibly,  lets agents reason, workflows execute, and guardrails enforce, with human-in-the-loop approvals and audit trails. It's vendor-neutral by design, sitting on top of whatever stack you own because it doesn't sell a SIEM or an endpoint. And AI SOC is just the start: use the pre-built solutions for threat hunting, threat intel, and malware analysis, or build your own for IAM, GRC, cloud security, vulnerability management, and detection engineering. Tomorrow's use case doesn't need a new vendor.

Where it's not the answer. If all you need is L1 triage relief on top of one SIEM and you have response handled, a pure-play like Dropzone is simpler and cheaper to start. If you're fully standardized on Falcon, CrowdStrike's native depth is hard to beat. If you want to build everything yourself on a low-code engine, Torq's simplified UI is a clean fit. BlinkOps is the answer when you want the triage speed of a pure-play and a platform to grow into across the whole of security operations, without stitching multiple vendors together.

Pricing model. Usage-based for the full platform, no module gating. You don't pay per log like the SIEM, per automation plus module like the SOAR-derived platforms, or per alert like the pure-plays, and you don't buy case management, SOAR, and AI SOC as separate line items. One usage-based price covers the whole platform. Exact numbers come via a conversation.

Score: 95 / ★★★★★. Highest on a rubric that values the full lifecycle, vendor neutrality, and platform breadth. Score it on triage alone and the gap narrows.

2. Torq: Best for Teams That Want to Build It Themselves on a Simplified UI

What it is. Torq started as a security hyperautomation platform and repositioned as an AI SOC platform. Its agentic layer, Socrates, coordinates specialized agents to triage, investigate, and respond on top of a mature workflow engine with around 300 integrations and 4,000+ pre-built steps (as of June 2026). Its Agentic Builder, for natural-language agent creation, is in beta.

Where it wins. A mature, low-code workflow engine with a simplified UI that makes building your own SOC solution approachable. The deterministic-plus-agentic combination is architecturally sound. Strong fit for teams that want to construct and own their automation rather than take a vendor's agents as-is, and that have the appetite to build on a platform rather than buy a finished one.

Where it falls short. No plug-and-play AI SOC. You build the SOC solution on the platform, which means time and engineering before value. The agent builder is still in beta as of June 2026, so judge it on what is in production today, not the roadmap.

Pricing model. Per-automation plus module. The bill grows as you add automations and turn on modules. Exact numbers via sales.

Score: 77 / ★★★★. The strongest pick for teams that want to build it themselves on an approachable, low-code platform.

3. Swimlane: Best for MSSPs Investing in Heavy Platform Engineering

What it is. Swimlane's Turbine platform is a low-code automation engine built for scale, with Hero AI for agentic features and an agent builder that arrived in beta in early 2026. Its roots are in legacy SOAR, and it has expanded into adjacent solutions like business continuity and vulnerability response.

Where it wins. Genuinely high-throughput automation pipelines, strong for very large alert volumes. The depth and flexibility reward teams, particularly MSSPs, that are willing to invest in heavy engineering of the platform to build exactly what they need across many tenants. Flexible deployment, including self-hosted for data-sensitive environments.

Where it falls short. Much of the agentic capability is still maturing out of beta, so it reads as AI layered onto a mature automation platform rather than agent-native. Realizing the value takes serious engineering investment, which is the opposite of plug-and-play. If you don't have the engineering capacity, you won't get the platform's worth out of it.

Pricing model. Per-automation plus module, scoped by automation volume and tier. Exact numbers via sales.

Score: 73 / ★★★★. Built for MSSPs and large teams that will invest the engineering to make a powerful platform their own.

4. Exaforce: Best for Cloud and SaaS-Heavy Environments

What it is. Exaforce is built around a proprietary multi-model engine (semantic, behavioral, and knowledge layers) rather than an LLM-only approach. Its Exabots run full-lifecycle investigation, and it offers both SaaS and managed models, positioned strongly for cloud and SaaS telemetry.

Where it wins. The multi-model architecture is a real differentiator; it isn't a single LLM with a prompt. Strong on cloud and SaaS investigation. Full-lifecycle ambition rather than triage-only. Vendor-neutral, with the flexibility to run as product or managed service.

Where it falls short. Case management and deterministic workflow support are limited. No agent builder, so you take the vendor's agents as-is. The model leans toward investigation and escalation rather than deep, governed response across an arbitrary stack. Younger company, so weigh platform-bet risk.

Pricing model. Per-alert, or managed-service pricing. SaaS or managed options.

Score: 68 / ★★★★. The standout if your environment is cloud and SaaS-first and you want investigation beyond LLM summarization.

5. Intezer: Great for Forensic-Grade Investigation of Every Alert

What it is. Intezer Forensic AI SOC is an autonomous SOC analyst that fully automates Tier 1 triage. It investigates every alert at forensic depth, combining endpoint forensics, reverse engineering, memory scanning, network artifact analysis, and sandboxing with multiple AI models, and it feeds outcomes back into SIEM and EDR detection rules through continuous detection engineering.

Where it wins. The forensic depth is the differentiator. This is real reverse engineering, memory analysis, and sandboxing, not an LLM summarizing an alert, which gives it the most investigation rigor of any pure-play here. It investigates 100% of alerts regardless of severity, with sub-minute triage and most false positives resolved in under a minute. Continuous detection engineering turns investigation outcomes into better SIEM and EDR rules over time. It's vendor-neutral, and verdicts are challengeable in the platform, so analysts can audit the reasoning rather than accept a black-box answer.

Where it falls short. No agent builder, so you take the vendor's models as-is. The heritage is endpoint and file forensics, so it's strongest on endpoint, phishing, and SIEM alerts and lighter as a general workflow platform. No real response orchestration layer; it investigates, recommends remediation, and escalates, but pairs with a SOAR for actual response. Case management is limited.

6. Prophet Security: Best for Investigation Depth and Visible Reasoning

What it is. Prophet positions itself as a comprehensive agentic AI SOC platform spanning detection engineering, investigation, threat hunting, and incident response. It emphasizes showing its reasoning, with evidence-based reports where you can see how the AI reached a verdict.

Where it wins. Visible reasoning, which builds analyst trust faster than a black-box verdict. Broader ambition than triage alone, reaching into detection engineering and hunting. Vendor-neutral, and strong for teams that want to audit the AI's logic rather than just accept its output.

Where it falls short. No agent builder. Case management is limited. Integration count is modest (around 49 as of June 2026). As with the group, response depth is the weak point; it explains beautifully but the orchestrated-response loop is thin compared to a SOAR-based platform.

Pricing model. Per-alert, typically as an enterprise contract that absorbs volume variance.

Score: 65 / ★★★★. The pick when analyst trust and investigation transparency matter most, paired with a response layer.

7. Dropzone AI: Best for Fast, Low-Friction Triage

What it is. Dropzone is an autonomous AI SOC analyst that investigates alerts end to end without playbooks. You point it at your SIEM, EDR, and other alert sources, and it returns a verdict. It reports 300+ deployments, with roughly 90 integrations (as of June 2026).

Where it wins. Genuinely fast to deploy, often day one. Strong investigation quality on common alert types; this is a good product at the job it's built for. Read-only, low-friction, vendor-neutral onboarding. Per-investigation pricing is the most predictable model in the pure-play space for steady-state flows.

Where it falls short. No agent builder, so you take the vendor's agents as-is. Case management is basic and not customizable. No real response layer, so the investigation-to-response handoff needs a separate SOAR or case tool. Limited to about 90 integrations and lives mainly on top of the SIEM.

Pricing model. Per-investigation. Predictable for stable volumes, but model your alert flow carefully so spikes don't surprise you.

Score: 63 / ★★★★. Excellent first AI SOC purchase for a team that wants triage relief fast and has response handled elsewhere.

8. CrowdStrike: Best for Falcon-Standardized Organizations

What it is. CrowdStrike has built a full agentic stack on the Falcon platform: Charlotte AI for detection triage and investigation, Charlotte AI AgentWorks (a no-code agent builder), Charlotte Agentic SOAR for orchestration, and Falcon next-gen SIEM. Charlotte AI Detection Triage is trained on Falcon Complete MDR analyst decisions.

Where it wins. If you already run Falcon, the AI capabilities are deep, native, and require no new vendor. Charlotte AI is trained on real elite-analyst decisions, which shows in triage quality. AgentWorks gives you an agent builder, and Agentic SOAR gives you orchestration. It's a genuinely full stack from one vendor.

Where it falls short. The value is strongest inside the Falcon ecosystem. The more of your stack lives outside CrowdStrike, the less the bundled economics and native context work for you. This is a platform-consolidation play, which means ecosystem lock-in. If you're multi-vendor by design, a vendor-neutral layer fits better.

Pricing model. Per-log ingest for the next-gen SIEM, plus per-module and per-agent pricing across the suite. Bundled economics if you're already a customer, but scaling can be opaque.

Score: 62 / ★★★★. A capable full stack, ranked below the vendor-neutral options here because its value is tied to the Falcon ecosystem. Standardize on Falcon and it ranks higher for you.

9. Google SecOps: Best for Chronicle and Google Cloud Teams

What it is. Google SecOps combines Chronicle SIEM with the former Siemplify SOAR and Gemini-powered AI for triage and investigation, shipping roughly 300 SOAR integrations and moving toward agentic capabilities.

Where it wins. Excellent if you're centralized on Google Cloud and Chronicle. Strong data and analytics foundation. Gemini integration for AI-driven triage and natural-language investigation. Native fit with the Google security portfolio.

Where it falls short. The Siemplify SOAR has been deprioritized since the acquisition, and the SOAR capability today reads as fairly basic, more case management than deep orchestration. AI SOC works best when you send everything to the platform, which has cost implications. Strong on detection and analytics, thinner on governed response.

Pricing model. Per-log and consumption-based, tied to data volume and Google Cloud.

Score: 61 / ★★★★. A natural fit for Google Cloud shops, ranked below the vendor-neutral options on lock-in and a thin response layer.

11. Radiant Security: Best for Mid-Market Alert Overload

What it is. Radiant delivers AI-driven triage and investigation that adapts regardless of alert type, auto-closing false positives and escalating real threats with context. It's purpose-built for the L1 triage problem.

Where it wins. Effective at the core mid-market pain: too many alerts, not enough analysts. Adaptive triage rather than rigid per-alert logic. Around 140 integrations, broader than several peers. Strong noise reduction. Vendor-neutral.

Where it falls short. Like the rest of the group, case management is basic and not customizable, there's no real response orchestration layer, and there's no agent builder. It's a strong triage product, not a platform.

Pricing model. Per-alert, sales-led, no published trial.

Score: 54 / ★★★. A solid mid-market choice when the immediate problem is alert volume and you want fast relief without building anything.

Q5. How Do the Top AI SOC Vendors Compare on Capabilities?

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"Limited" means partial or early-stage; for case management it means basic and not customizable. Deployment model and agent builder are in the Q2 table. Integration counts are as of June 2026.

Notable Vendors Not Included

Three vendors frequently appear in other AI SOC comparison lists but are not in our top 10:

Palo Alto Networks (Cortex XSIAM): A strong platform, but it's an XDR/SIEM consolidation play rather than a standalone AI SOC. Its value is heavily tied to the Palo Alto ecosystem, and the pricing model (per-endpoint plus data ingest) creates significant lock-in. On a vendor-neutral rubric, it ranks similarly to the SIEM-bundled category.

SentinelOne: Primarily an endpoint-first platform with AI capabilities layered on its Singularity platform. Strong at endpoint detection but limited as a multi-vendor SOC orchestration layer.

Stellar Cyber: An Open XDR platform with AI SOC features. Good for mid-market buyers looking for an all-in-one, but the AI SOC layer is ancillary to the XDR product rather than the core offering.

These vendors may be the right choice depending on your environment. They didn't make our top 10 because our rubric weights vendor neutrality and full-lifecycle coverage heavily, and these platforms are strongest within their own ecosystems.

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Q6. How Should You Compare Pricing Across AI SOC Vendors?

No vendor in this market publishes real pricing, so ignore any comparison that prints a starting number. What matters is the pricing model, because that determines how your bill behaves as you scale, and because most of these models charge you for one slice of the workflow while you still buy the rest separately.

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Why BlinkOps is the best value, plainly. Every other model on this list charges you for a fragment. The SIEM bills you per log. The SOAR-derived platforms bill you per automation and then again per module. The pure-plays bill you per alert. In all three cases you pay for one part of the job and then go buy the missing pieces, a separate case management tool, a separate SOAR, a separate response layer, each with its own contract. BlinkOps is usage-based for the whole platform: AI SOC, Agentic SOAR, case management, agent builder, and 30,000+ governed actions under one model, with no per-log penalty, no per-automation meter, and no per-alert spike. You are not assembling multiple vendors and multiple bills to get one working SOC.

Whatever model you are quoted, get these in writing before you sign: onboarding fees, SIEM migration or integration costs, professional-services charges for custom work, per-alert or per-automation surcharges above tier limits, module add-on fees, and any mandatory multi-year commitment.

Q7. What Is an Agentic AI SOC, and How Is It Different From Traditional MDR?

An agentic AI SOC uses AI agents that reason, decide, and act within guardrails, rather than a single LLM call that summarizes an alert. The agents have defined abilities and can take action, not just analyze. This is the term the market is converging on, replacing the looser "AI SOC."

The difference from traditional MDR is ownership and transparency. MDR outsources your operations to an external team and a black box; you get outcomes but limited visibility and control. An agentic AI SOC keeps operations in-house and, in the better implementations, shows its reasoning and lets you tune the agents. You trade the hands-off convenience of MDR for control, auditability, and the ability to adapt the system to your environment instead of waiting on a vendor's analysts.

The catch: many platforms calling themselves agentic still stop at investigation. A real agentic SOC closes the loop through to governed response, and that's the line separating a feature from a platform.

Q8. How Should You Choose the Right AI SOC Vendor?

Work through these in order. They map to the categories and the scoring rubric above.

Product or managed service? If you don't have a SOC team to oversee the AI, you want a managed offering, not a platform. Several vendors here offer both.

Buy a finished solution, or build your own? If you want triage working on day one, the plug-and-play options (BlinkOps, the pure-plays) get you there. If you want to construct and own your automation, a build-it-yourself platform (Torq's simplified UI, or Swimlane for MSSPs with engineering capacity) is the fit.

Triage only, or full lifecycle? If you just need L1 triage relief and response is handled elsewhere, a pure-play (Dropzone, Radiant) is faster and cheaper to start. If you need investigation and governed response on one platform, look at the SOAR-derived platforms, a SIEM-bundled stack, or an agentic platform like BlinkOps.

How heterogeneous is your stack? Standardized on one ecosystem (Falcon, Google Cloud)? The native option gives depth and bundled economics. Deliberately multi-vendor? A vendor-neutral layer avoids lock-in.

Do you need to extend beyond the SOC? If threat hunting, threat intel, malware analysis, IAM, GRC, and vulnerability management are on your roadmap, a platform that ships and builds solutions beyond AI SOC saves you from buying and integrating a new vendor every time.

How predictable is your alert volume? Per-alert and per-investigation models are predictable for steady flows but spike under load. Usage-based platform models give more budget certainty under variance.

Q9. Frequently Asked Questions

What is the best AI SOC platform in 2026? It depends on your stack and needs. For fast triage on an existing stack, Dropzone is strong. For Falcon shops, CrowdStrike's native depth is hard to beat. For teams that want to build their own SOC, Torq's simplified UI is a clean fit. For an agentic platform where AI SOC is one of many solutions you can use or build, BlinkOps is built for that and ranks first on our vendor-neutral, full-lifecycle rubric. Re-weight the rubric for a triage-only or single-ecosystem need and the order changes.

How much does an AI SOC platform cost? No vendor publishes real pricing; numbers in most comparisons are invented. What matters is the model, because each charges for a different slice of the workflow: per-log for the SIEM (Google SecOps, CrowdStrike), per-automation plus module for the SOAR-derived platforms (Torq, Swimlane, D3), and per-alert for the pure-plays (Dropzone, Prophet, Exaforce, Radiant). BlinkOps is the one usage-based model that covers the full platform, so you don't pay per log, per automation, or per alert, and you don't buy the missing pieces separately.

Do AI SOC platforms replace human analysts? No. They replace repetitive triage and investigation work so analysts focus on judgment, hunting, and high-impact decisions. The better platforms keep humans in the loop on high-impact actions by design.

What's the difference between AI SOC and SOAR? SOAR automates predefined response workflows (playbooks). AI SOC uses AI to investigate alerts and reach verdicts. The strongest platforms combine both: agents reason, deterministic workflows execute, guardrails enforce. Treating them as either/or is a mistake.

Can an AI SOC platform work without sending all my data to one SIEM? SIEM-bundled AI SOC works best when you centralize data in that vendor's platform, which has cost implications. Vendor-neutral platforms work across your existing stack without forcing centralization. If you're multi-vendor, weigh this carefully.

Is AI SOC the only thing these platforms do? For most of them, yes, or close to it. The pure-plays do triage and investigation. The SOAR-derived platforms do automation and response. BlinkOps is the exception on this list: AI SOC is one solution among many, alongside pre-built solutions for threat hunting, threat intel, and malware analysis, plus the ability to build custom solutions for IAM, GRC, and more on the same platform.

What MITRE ATT&CK coverage do AI SOC platforms provide? Most AI SOC platforms don't publish formal MITRE ATT&CK coverage maps the way endpoint vendors do. The practical answer: pure-play platforms cover the techniques their investigation models were trained on, which skew toward common alert types (credential access, lateral movement, command and control). Broader platforms like BlinkOps and CrowdStrike cover more techniques because they span more of the SOC workflow. Ask any vendor for a coverage matrix before you buy; if they can't provide one, that's a signal.

What is the ROI of an AI SOC platform? The primary ROI comes from three places: (1) analyst time recovered by automating L1 triage, (2) reduced mean time to respond (MTTR), and (3) fewer tools and contracts needed when the platform covers investigation, response, and case management under one roof. For most teams, the highest-value metric is the number of alerts fully resolved without human touch. A strong AI SOC platform should handle 80–95% of Tier 1 alerts autonomously.