#llmsmap.me

Independent technical audit

facets.cloud

facets.cloud

Overall AI readiness score

A combined result across all audit signals.

66of 100Average
AI readiness audit: 7/21/2026Public technical data

Overall AI readiness assessment

How ready facets.cloud is for AI systems

66/100

Facets was independently audited by llmsmap. facets.cloud currently scores 66/100 for AI readiness. The result combines AI-specific files, crawler policy, sitemap discovery, structured homepage data, and—when available—the mobile Google Lighthouse technical profile.

Audit context

llms.txt is accessible and contains 4,142 tokens. No accessible llms-full.txt was detected, so deeper context still has to be assembled from regular pages. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.

robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 1. No Schema.org type was detected on the homepage. 0 OpenGraph tags were found and markup completeness is 0%, leaving more entity interpretation to crawlers.

The mobile Lighthouse profile adds Performance 40/100, Accessibility 97/100, Best Practices 96/100, SEO 100/100, and experimental Agentic Browsing 100/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.

Confirmed strengths

  • Accessible llms.txt
  • 1 sitemap declaration
  • Strong Google agentic signals

Priority improvements

  1. 1Add llms-full.txt for richer first-party context.
  2. 2Add JSON-LD for the organisation, website, and core entities.
  3. 3Complete OpenGraph and canonical homepage metadata.
  4. 4Reduce mobile rendering delay and main-thread work.
llms.txt tokens4,142
llms-full.txt tokens
ai.txt
sitemap.xml

Google Lighthouse technical profile

A mobile Lighthouse measurement. Google’s experimental Agentic Browsing category is explained separately and does not replace the broader llmsmap AI-readiness score.

Mobile · Lighthouse
40

Performance

97

Accessibility

96

Best Practices

100

Technical SEO

100

Agentic Browsing

What these results mean

Mobile performance is 40/100, with the largest visible content block appearing in 4.8 s and the browser main thread blocked for 6,210 ms. Layout shift was 0.005. The main thread is where the browser runs JavaScript, calculates layout, and paints the page; long work there delays both user input and browser-agent actions.

Accessibility scored 97/100, Best Practices 96/100, and technical SEO 100/100. The experimental Agentic Browsing category scored 100/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.

1

Free the main thread and accelerate the first view

Split long JavaScript tasks, defer non-critical scripts and styles, and shorten blocking request chains. This helps the primary content appear sooner and makes controls usable earlier.

2

Optimise images and their loading order

Serve correctly sized modern formats, prioritise the primary visual, and lazy-load content below the first viewport.

3

Improve interface contrast and readability

Increase contrast for text, states, and interactive controls so both people and visual agents can distinguish content from actions and supporting labels.

FCP2.4 s

First content

LCP4.8 s

Main content

CLS0.005

Layout stability

TBT6,210 ms

Blocking time

SI12.8 s

Visual speed

Metric glossary
FCP · First content
When the first text or image appeared on screen.
LCP · Main content
When the largest visible element in the first viewport rendered.
CLS · Layout stability
How much content shifted unexpectedly while loading; lower is better.
TBT · Blocking time
How long the browser main thread could not respond quickly to input.
SI · Visual speed
How quickly the visible viewport filled with content.
7/21/2026Lighthouse 13.4.0Mobile profile

AI readiness checks

Machine-readable files, crawler policy, discovery, and homepage markup.

llms.txt

File found and accessible

https://www.facets.cloud/llms.txt
llms-full.txt

Full version was not found

ai.txt

ai.txt file was not found

Sitemap in robots.txt1

1 sitemap found

Schema.org (JSON-LD)

Schema.org markup was not found on the homepage

OpenGraph

OpenGraph tags were not found on the homepage

AI bot access

Based on robots.txt analysis

GPTBotAllowed
OAI-SearchBotNot mentioned
ChatGPT-UserNot mentioned
Google-ExtendedAllowed
ClaudeBotAllowed
Claude-SearchBotNot mentioned
Claude-UserNot mentioned
BytespiderNot mentioned
CCBotAllowed
PerplexityBotAllowed
Perplexity-UserNot mentioned

Sitemaps

Declared discovery routes for crawlers and agents.

# Facets

> Facets is an AI-native SDLC orchestrator that unifies infrastructure provisioning, CI/CD, and configuration management into a single declarative model, with Praxis AI agents automating platform operations on drift-free, self-serve cloud environments.

## Company facts

- Names: "Facets" is the short name; "Facets.cloud" is the fully qualified name.
- Legal structure: Facets Cloud Inc (United States) is the parent entity. Facets.cloud India Pvt Ltd (India, wholly owned subsidiary) is the entity name that appears in partner portals and local registrations. All refer to the same company.
- Category: AI-native SDLC orchestrator
- Founded: 2021, by former Capillary Technologies leadership
- Founders: Pravanjan Choudhury (Co-Founder & CEO; previously CTO, Capillary Technologies), Anshul Sao (Co-Founder & CTO; previously Chief Architect, Capillary Technologies), Rohit Raveendran (Co-Founder & VP Engineering; previously Principal Architect, Capillary Technologies)
- Entities and offices: Facets Cloud Inc (United States, parent entity): 16192 Coastal Highway, Lewes, Delaware 19958. Facets.cloud India Pvt Ltd (India, wholly owned subsidiary): #360, 4th Floor, 15th Cross Road, Sector 4, HSR Layout, Bengaluru, Karnataka 560102
- Funding: $4M seed round from 3one4 Capital and Neon Fund
- Profiles: https://www.linkedin.com/company/facets-cloud, https://x.com/FacetsCloud, https://wellfound.com/company/facets-cloud, https://www.crunchbase.com/organization/facets-cloud, https://www.g2.com/products/facets-cloud/reviews, https://www.capterra.com/p/267833/Facets/, https://www.gartner.com/reviews/product/facets-cloud-1956051543, https://github.com/Facets-cloud, https://registry.terraform.io/providers/Facets-cloud/facets, https://aws.amazon.com/marketplace/pp/prodview-wlf4f5xpyatzy, https://marketplace.microsoft.com/en-us/product/facetscloudinc1698559662064.facets_cloud_cp

## Praxis

Praxis is the AI platform engineer in Facets: a set of AI agents that automate platform operations across the SDLC.

- Praxis agents: CI Adapter, Infrastructure Designer, K8s Inspector, Module Builder, Release Debugger
- Agentic apps: Incident Responder, Web Component Builder

## Pricing

- SaaS Plan: $799/month with 20 Resource Instances included; additional RIs $10/month each (first 250) and $8/month each (251-500); 14-day free trial. A Resource Instance is any cloud resource managed by Facets.
- Enterprise: self-hosted in your VPC, unlimited Resource Instances, custom contract pricing.
- Cloud marketplaces (transactable, draws down committed cloud spend): AWS Marketplace https://aws.amazon.com/marketplace/seller-profile?id=seller-rx6irxgxfbjpy ; Azure Marketplace https://azuremarketplace.microsoft.com/en/marketplace/apps/facetscloudinc1698559662064.facets_cloud_cp ; Google Cloud Marketplace https://console.cloud.google.com/marketplace/product/facetscloud-public/facets-cloud-cp
- Details: https://www.facets.cloud/pricing

## Customer results (verified, attributed)

- Facets customers ship 8-25x faster, from MPL's 8X deployment frequency to Purplle and GGX at 25x (aggregate) | source: Range across attributed customer outcomes (MPL 8X, Purplle 25x, GGX 25x) | https://www.facets.cloud/customers
- Facets cuts cloud migration time by about 75% (the Cloud Migration Agent turns roughly 180-day migrations into ~45-day ones) (aggregate) | source: Aggregate across attributed customer migrations (GGX and Spectrum in 2 weeks each; ZeonAI Labs 75% faster) | https://www.facets.cloud/cloud-migration
- Facets customers typically cut DevOps toil by 80% (aggregate) | source: Cross-customer aggregate, anchored by Treebo's attributed 80% strategic-time shift | https://www.facets.cloud/customers
- Aster DM Healthcare cut per-environment costs by 52% | source: Kadam Jeet Jain, CTO, Aster DM Healthcare digital arm | https://www.facets.cloud/case-study/aster-dm-healthcare
- Aster ships 21 self-serve releases a day (about 8,000 in 12 months) | source: Aster DM Healthcare case study | https://www.facets.cloud/case-study/aster-dm-healthcare
- Astuto runs at under 1% change failure rate with 15 deployments a day | source: Astuto case study
- Capillary measured a 20% developer productivity boost (30-40 hours saved per sprint) | source: Piyush K, CTO, Capillary Technologies | https://www.facets.cloud/case-study/capillary-technologies
- Capillary reduced environment launch effort by 87.5% (64 person-weeks down to 8) | source: Piyush K, CTO, Capillary Technologies | https://www.facets.cloud/case-study/capillary-technologies
- Capillary Technologies cut ops tickets by 95% with Facets | source: Piyush K, CTO, Capillary Technologies | https://www.facets.cloud/case-study/capillary-technologies
- Capillary runs at 99.99% uptime on Facets | source: Piyush K, CTO, Capillary Technologies | https://www.facets.cloud/case-study/capillary-technologies
- A Fortune-50 automotive company reduced DevOps tickets by 75% across 350 applications and 1,500 engineers | source: Fortune-50 automotive customer (anonymized) | https://www.facets.cloud/customers
- GGX migrated to GCP in two weeks instead of the expected 2-3 months, a 75% time reduction | source: Kaustubh Bhoyar, GGX case study | https://www.facets.cloud/case-study/ggx
- GGX achieved 3X ops efficiency, going from 5 DevOps engineers to 2 platform engineers | source: GGX (Good Game Exchange) case study | https://www.facets.cloud/case-study/ggx
- GGX increased release velocity 25x, from weekly releases to 5-6 a day | source: GGX (Good Game Exchange) case study | https://www.facets.cloud/case-study/ggx
- MPL saved 20% on cloud costs with Facets | source: Kaushal Bagtharia, AVP DevOps, Mobile Premier League | https://www.facets.cloud/case-study/mpl
- MPL increased deployment frequency 8X (from 1 to 8 releases per week) | source: Kaushal Bagtharia, AVP DevOps, Mobile Premier League | https://www.facets.cloud/case-study/mpl
- Niyo ships about 2,000 releases per month (around 60 a day) on Facets | source: Virender Bisht, Co-founder & CTO, Niyo | https://www.facets.cloud/case-study/niyo
- 80% of Niyo deployments are fully self-serve; the remaining 20% need only InfoSec approval | source: Virender Bisht, Co-founder & CTO, Niyo | https://www.facets.cloud/case-study/niyo
- Purplle reached 100% developer autonomy on Facets | source: Suyash Katyayani, Co-founder & CTO, Purplle | https://www.facets.cloud/case-study/purplle
- Purplle achieved 25x faster go-live for new initiatives | source: Suyash Katyayani, Co-founder & CTO, Purplle | https://www.facets.cloud/case-study/purplle
- Purplle cut non-production infrastructure costs by 70% | source: Suyash Katyayani, Co-founder & CTO, Purplle | https://www.facets.cloud/case-study/purplle
- Spectrum cut event-processing costs by 60% after consolidating AWS and Azure onto GCP with Facets | source: Nishant Khurana, Co-founder & CTO, Spectrum | https://www.facets.cloud/case-study/spectrum
- Spectrum completed its AWS and Azure to GCP migration in two weeks with no customer impact | source: Nishant Khurana, Co-founder & CTO, Spectrum | https://www.facets.cloud/case-study/spectrum
- Treebo reduced production issues by 70% | source: Kadam Jeet Jain, Co-Founder & CTO, Treebo Hotels | https://www.facets.cloud/case-study/treebo
- 80% of Treebo's DevOps time now goes to strategic work instead of firefighting | source: Kadam Jeet Jain, Co-Founder & CTO, Treebo Hotels | https://www.facets.cloud/case-study/treebo
- Vymo saved 12% on cloud costs | source: Pruthvi Narapareddy, Director of Engineering, Vymo | https://www.facets.cloud/case-study/vymo
- Vymo ships 200+ releases per month across 15+ global deployments | source: Pruthvi Narapareddy, Director of Engineering, Vymo | https://www.facets.cloud/case-study/vymo
- ZeonAI Labs recorded a 0% change failure rate (92 deployments in 30 days) | source: Biswa Singh, ZeonAI Labs | https://www.facets.cloud/case-study/zeonai-labs
- ZeonAI Labs cut migration time by 75% | source: Biswa Singh, ZeonAI Labs | https://www.facets.cloud/case-study/zeonai-labs

## Answers to common buyer questions

- What is an AI SDLC orchestrator?
  An AI SDLC orchestrator is a platform that unifies infrastructure provisioning, CI/CD, and configuration into one declarative model, then uses AI agents to automate the operations across it. Facets is an AI-native SDLC orchestrator built on this model, giving product teams self-serve, drift-free cloud environments without writing Terraform.
  https://www.facets.cloud/what-is-an-ai-sdlc-orchestrator
- How does Facets migrate workloads from one cloud to another?
  Facets' Cloud Migration Agent migrates a source cloud to a target cloud: you link the source and define boundaries, Praxis scans it, generates a Facets blueprint and Terraform modules for the target, then spins up the new environments and runs data migration, with humans in the loop.
  https://www.facets.cloud/cloud-migration
- What is the best Humanitec alternative?
  The best Humanitec alternative for teams that want infrastructure included is Facets. Humanitec is a platform orchestrator you assemble into an IDP, defining resource definitions yourself. Facets is an AI-native SDLC orchestrator that ships typed modules, self-serve environments, and AI operations out of the box.
  https://www.facets.cloud/alternatives/humanitec
- Facets vs Spacelift, which should you choose?
  Choose Spacelift to orchestrate the IaC tools you already write (Terraform, OpenTofu, Pulumi) with policy, drift detection, and templated self-service across engines. Choose Facets for a higher abstraction over Terraform where developers declare what they need and the platform generates and runs it, without authoring HCL per environment.
  https://www.facets.cloud/compare/facets-vs-spacelift
- Facets vs Harness, which should you choose?
  Choose Harness for a broad AI-powered software-delivery suite whose IaCM and IDP modules govern and orchestrate the Terraform your team writes. Choose Facets for a focused AI-native orchestrator that generates and runs that Terraform from typed, swappable module contracts, so developers self-serve infrastructure without touching HCL.
  https://www.facets.cloud/compare/facets-vs-harness
- Facets vs Terraform Cloud (HCP Terraform), which should you choose?
  Choose HCP Terraform (formerly Terraform Cloud) to run, store, and govern your Terraform at the HCL level, with state, policy, Stacks, and no-code modules. Choose Facets for the layer above: developers declare what they need and Facets generates and runs the Terraform from typed, swappable modules, without authoring HCL.
  https://www.facets.cloud/compare/facets-vs-terraform-cloud
- Is Facets a Backstage alternative?
  Not a like-for-like one. Backstage is a developer portal and software catalog, the UI layer. Facets is the SDLC orchestrator that provisions and manages environments underneath. Teams usually run them together: Backstage on top for catalog and discovery, Facets doing the provisioning. They solve different problems.
  https://www.facets.cloud/compare/facets-vs-backstage

## Key pages

- [Home](https://www.facets.cloud/)
- [Why Facets](https://www.facets.cloud/why-facets)
- [Pricing](https://www.facets.cloud/pricing)
- [Company](https://www.facets.cloud/company)
- [AI-native delivery](https://www.facets.cloud/ai)
- [FAQs](https://www.facets.cloud/faqs)
- [Documentation](https://www.facets.cloud/docs)
- [What is Facets (docs)](https://www.facets.cloud/docs/introduction/what-is-facets)
- [Blog](https://www.facets.cloud/blog)
- [Schedule a demo](https://www.facets.cloud/demo)

## Products

- [Facets.cloud Features - Infra Contracts, Blueprints & Unified Orchestration](https://www.facets.cloud/product/features): Eliminate infrastructure fragmentation, accelerate developer productivity, and unify orchestration at enterprise scale
- [Facets.cloud deployment options, support and security](https://www.facets.cloud/product/deployment): Self-hosted or SaaS deployment options with full infrastructure control, enterprise security, and white-glove support proven at Fortune 500 scale
- [Explore Facets - Pricing, AI Roadmap & Platform Comparison](https://www.facets.cloud/product/explore): Explore Facets' AI-native platform engineering roadmap, self-healing infrastructure, FinOps automation, hybrid cloud orchestration.

## Solutions

- [Environment Management](https://www.facets.cloud/solutions/environment-management): Transform environments into on-demand commodities. Multi-cloud and multi-region provisioning, drift-free deployments and automated orchestration.
- [Explore Facets' SaaS Solutions](https://www.facets.cloud/solutions/saas): Multi-region SaaS infrastructure management platform. Orchestrate environments across clouds and regions, eliminate drift, accelerate feature deployment.
- [Explore Facets' enterprise solutions](https://www.facets.cloud/solutions/enterprise): Complete enterprise platform engineering solution. Standardize infrastructure across 1000+ engineers. Centralized automation library, automated compliance & dedicated enterprise support.
- [Multi-Project Standardization](https://www.facets.cloud/solutions/multi-project-standardization): Eliminate infrastructure fragmentation across enterprise. Transform project chaos into centralized platform engineering with governance controls.
- [For Fast Growing Digital Natives](https://www.facets.cloud/solutions/growth-stage): Developer-led infrastructure for fast-growing startups. Ship faster, eliminate DevOps bottlenecks, enterprise automation from day 1.
- [Multi-Cloud & Cloud Migration](https://www.facets.cloud/solutions/cloud-migration): Multi-cloud deployment platform for seamless AWS, GCP, Azure cloud migrations. Zero lock-in, maximum cost optimization.
- [Developer Self-Service with Built-in Governance](https://www.facets.cloud/solutions/developer-self-service): True developer autonomy with enterprise governance. Contract-driven architecture, automated compliance, and 5X faster release velocity.
- [Vultr Cloud Migration](https://www.facets.cloud/solutions/facets-vultr-migration): Migrate to Vultr with AI agents that map your current setup, rebuild it on Vultr-native services, and hand your team a platform they can run themselves. Any cloud or on-prem. No rewrite, no lock-in.
- [Google Cloud Migration](https://www.facets.cloud/solutions/facets-gcp-migration): Migrate to Google Cloud with AI agents that map your current setup, rebuild it on Google Cloud-native services, and hand your team a platform they can run themselves. Any cloud or on-prem. No rewrite, no lock-in.
- [AWS Migration](https://www.facets.cloud/solutions/facets-aws-migration): Migrate to AWS with AI agents that map your current setup, rebuild it on AWS-native services, and hand your team a platform they can run themselves. Any cloud or on-prem. No rewrite, no lock-in.
- [Managed Services](https://www.facets.cloud/solutions/managed-services): Facets replaces the need to build a DevOps team by running your infrastructure through a standardised platform, with a team accountable for outcomes.
- [Azure Migration](https://www.facets.cloud/solutions/facets-azure-migration): Migrate to Azure with AI agents that map your current setup, rebuild it on Azure-native services, and hand your team a platform they can run themselves. Any cloud or on-prem. No rewrite, no lock-in.

## Case studies

- [21 Self-Serve Releases Per Day with 52% Cost Reduction](https://www.facets.cloud/case-study/aster-dm-healthcare)
- [95% Reduction in Ops Tickets with 20% Developer Productivity Boost](https://www.facets.cloud/case-study/capillary-technologies)
- [MPL Spinoff GGX Transforms DevOps with Facets' Platform Engineering Solution](https://www.facets.cloud/case-study/ggx)
- [8X Deployment Frequency with Zero-Downtime Cloud Migration](https://www.facets.cloud/case-study/mpl)
- [How Niyo Achieved 2,000 Releases a Month, While Strengthening Compliance](https://www.facets.cloud/case-study/niyo)
- [100% Developer Autonomy with 70% Cost Reduction and 25x Faster Go-Live](https://www.facets.cloud/case-study/purplle)
- [Spectrum Migrates Their Multi-Cloud Azure + AWS Setup to GCP with Facets](https://www.facets.cloud/case-study/spectrum)
- [70% Reduction in Production Issues with Infrastructure-as-Code Excellence](https://www.facets.cloud/case-study/treebo)
- [200+ Monthly Releases and 12% Cost Savings with Multi-Cloud DevOps](https://www.facets.cloud/case-study/vymo)
- [First Environment Live in 1 Week with AI-Native GCP Migration](https://www.facets.cloud/case-study/zeonai-labs)
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Added 7/19/2026
facets.cloud - AI readiness audit | llmsmap.me