Entanglreview, pricing and limits

For data center operations teams whose procedures drift from as-built reality, Entangl swaps manual document review for an AI agent trained on the facility's own design data. There is no self-serve signup: onboarding starts with a sales-led bootcamp, run by a team of roughly a dozen people as of 2026.

Entangl is an AI agent, founded in 2024 by two former reusable-rocket engineers, that generates and cross-checks data center operating procedures against a facility's own design and engineering data. It also monitors live operations to detect issues and triage alarms, catching circuit and sequencing errors before a technician executes a procedure.

Maker: Entangl, Inc. · Autonomy: semi autonomous · Maturity: GA

Underlying models: Custom (proprietary)

About Entangl

Entangl is an AI agent built by Entangl, Inc. for data center engineering and operations teams. Founded in San Francisco in 2024 by Shapol M and Antanas Zilinskas, two engineers who previously led a reusable rocket program through four launches, the founders built their own internal engineering error-checking tool before turning it into a product. Entangl went through Y Combinator's Summer 2024 batch and has since grown to roughly a dozen employees serving data center operators who need to catch design and procedural mistakes before they cause downtime. The product works by ingesting a data center's own design and engineering documentation, wherever it already lives across tools like GitHub, Google Drive, and OneDrive, then generating and reviewing Method of Procedure, Standard Operating Procedure, and Emergency Operating Procedure documents against that source data. It flags circuit continuity errors, sequencing mistakes, dependency errors, and administrative or safety-protocol gaps in a proposed procedure before a technician executes it, and separately monitors live operations to detect issues and triage alarms in real time. That combination, cross-checking paperwork against the facility's actual engineering data while also watching operations as they happen, is what separates Entangl from a static document-management tool: it acts on the data center's own source of truth rather than a generic checklist. Entangl is built for data center operations engineers, facility managers, and reliability teams at colocation and hyperscale operators who write and execute MOPs and EOPs as part of routine maintenance and incident response. It is not aimed at individual developers or small teams; the product assumes an organization already running a staffed data center with its own engineering documentation to ingest. Entangl does not publish self-serve pricing. Access starts with an on-site bootcamp, where the Entangl team sets the platform up against a prospect's own data center systems so the customer's engineers can test it live before signing a contract. There is no public free tier; deals are enterprise and sales-led, delivered as a cloud-hosted web platform. The company continues to hire across engineering, sales, and what it calls its 'experiment team,' and lists live reviews on G2 under an automated error-detection-and-correction listing, evidence of paying customers in production rather than a pre-launch prototype. Given its small team size and lack of a published changelog, treat Entangl as an early-stage but operationally deployed platform rather than a mature, frequently shipping product.

Pricing

Entangl does not publish public pricing. Every deal starts with an on-site bootcamp where the team configures the platform against the prospect's own data center design and engineering data so the customer can test it live before a contract is signed. There is no self-serve signup or published subscription tier as of 2026; pricing is enterprise and sales-led.

Key Features

• Procedure generation from real design data: Drafts MOP, SOP, and EOP maintenance documents directly from a data center's own engineering and design records instead of a generic template.
• Cross-checks procedures against source data: Flags circuit continuity errors, sequencing mistakes, and dependency errors in a draft procedure before a technician executes it inside a live facility.
• Real-time operations monitoring: Watches live data center operations to detect anomalies and triage alarms as they occur, rather than only reviewing paperwork after an incident.
• Knowledge base ingestion: Crawls engineering documentation scattered across GitHub, Google Drive, and OneDrive to surface design errors before they reach construction or deployment.
• Design-to-operations handover checks: Identifies deviations between a facility's baseline design and its as-built or as-operated state, catching gaps that would otherwise be lost during handover.
• On-site bootcamp onboarding: New customers set the platform up against their own facility's systems and data during an on-site bootcamp before committing to a contract.

Strengths

• Cross-checks operating procedures against a facility's actual design and engineering data rather than a generic template, catching circuit continuity and sequencing errors before they reach a technician.
• Founders previously ran a reusable rocket program through four launches, bringing safety-critical operations experience to a product deployed on infrastructure that global financial markets depend on.
• Listed on G2 as an automated error-detection product with a 4.8-star rating, evidence of paying customers running it in production rather than a pre-launch prototype.

Weaknesses

• No public pricing or self-serve signup; every deal starts with a sales-led on-site bootcamp, which slows evaluation for smaller operators who want to test the product first.
• Roughly a dozen employees and a single disclosed YC seed round as of 2026, a small team for a product monitoring critical infrastructure at scale.
• No published API documentation, changelog, or public integrations list, so prospective customers cannot verify integration depth with an existing BMS or DCIM stack before a sales call.

Visit Entangl Official Site