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AI Development for Drupal

Your Drupal platform already holds years of content, data and knowledge. We connect it to AI — building chatbots that answer from your own content, automating multilingual publishing, and making your pages visible to ChatGPT and Perplexity.

We have delivered AI in production on Drupal. Talk to us about your site.

Your Drupal site is falling behind AI-native competitors

Publishing at scale is getting harder without AI. Editors spend hours on translations, metadata and alt texts that AI can handle in seconds. Visitors expect instant answers, not a search box that returns ten links. Your content is also invisible to the LLMs people now use before Google.

The question isn't whether to adopt AI - it's how quickly you can implement AI solutions before the competitive gap becomes impossible to close.

What we build on Drupal with AI

These are not proofs of concept. Each capability below is live in production for Droptica clients.

Developer working on generative artificial intelligence at Droptica.

AI chatbot on your Drupal site

A chatbot that reads Drupal content in real time and answers in natural language. Built with RAG, it uses your content types, taxonomy and file library as the source of truth.

  • Multilingual answers in the visitor’s language.
  • Fallback to human support when confidence is low.
  • Drupal admin panel to review questions and improve answers.

AI on Drupal in production

ProjektMagazin.de uses a Drupal AI chatbot with RAG. BetterRegulation uses AI document categorization and AI summaries. Exide uses AI-assisted multilingual publishing workflows in Drupal.

AI document chatbot for ProjektMagazin.de.

A Drupal subscription platform needed faster access to hundreds of resources. We built a RAG chatbot that answers in natural language from Drupal content.

AI document categorization for BetterRegulation.

On a Drupal platform for regulatory content, AI extracts metadata and prepares summaries of long legal documents.

The development of AI agents is one of the AI solutions we offer our clients at Droptica.

Multilingual Drupal with AI translation

AI generates translations for configured languages directly in Drupal, field by field. Native reviewers approve or correct drafts in Drupal’s translation interface before publishing.

Editorial content automation with Drupal AI module

We configure Drupal AI providers, AI Interpolator, AI Automators and field-level prompts for alt texts, SEO metadata, content summaries and moderation assistance. Editors keep working in Drupal admin; AI prepares drafts and humans approve.

Cloud APIs

OpenAI, Anthropic, Google Gemini and DeepL are fast to set up for public content, translations, summaries and chatbots.

On-premise models

Llama, Mistral, Gemma, Qwen, DeepSeek, Bielik or PLLuM keep sensitive content inside your infrastructure.

Cloud and on-premise AI models — your choice

We do not lock you into one provider. Drupal AI can use cheaper models for bulk metadata, stronger models for translation quality, and local models where governance requires it.

The Droptica team, which develops generative artificial intelligence.

LLM visibility for Drupal content

We check whether your Drupal pages are cited by ChatGPT and Perplexity, restructure content for AI answers, add schema markup and monitor citation rates.

API costs are controlled by design

We use cheaper models for bulk work, stronger models where quality matters, cache results in Drupal and estimate volume upfront.

GDPR and data privacy stay in scope

We minimize data before API calls and deploy on-premise LLMs when content cannot leave your environment.

Our AI team creates AI solutions that identify patterns, detect anomalies, and predict future trends.

What we need to get started

The best AI projects start with one concrete use case: chatbot for documentation, automated alt texts, translation workflow, SEO metadata or LLM visibility.

How we implement AI on your Drupal site

We start small, test on real content, then move to production with monitoring, documentation and editor training.

Step 1: Research and strategy

We start with a discovery workshop to understand your business challenges, identify AI opportunities, and define success metrics aligned with your business objectives. Through detailed analysis of your workflows, data sources, and existing systems, we create a tailored AI strategy and implementation roadmap.

Step 2: Architecture and planning

Our team designs the technical architecture for your AI solution: selecting optimal AI models (GPT, Claude, open-source LLMs), planning integrations with your systems, and defining data pipelines. Data preparation strategies ensure your AI models have quality input. We create detailed project specifications, timelines, and resource allocation.

Step 3: Prototype and Proof of Concept

Before full development, we build a working prototype to validate the approach. This rapid proof-of-concept demonstrates core functionality, identifies potential challenges early, and ensures the AI solution meets your expectations before significant investment.

Step 4: Development and integration

Our developers build production-ready AI solutions with clean code, comprehensive documentation, and best practices. We integrate AI models with your existing systems (CRM, databases, APIs), implement security measures, and optimize for performance and cost.

Step 5: Testing and Quality Assurance

Rigorous testing ensures your AI solution works reliably in production. We conduct security testing (prompt injection, data leaks), performance optimization, edge case handling, and user acceptance testing. Automated checks and manual QA catch issues before deployment.

Step 6: Deployment and launch

We deploy your AI solution to production infrastructure with zero-downtime releases. Comprehensive monitoring, error tracking, and performance metrics ensure smooth operation. Team training and knowledge transfer help your staff use and maintain the system.

Step 7: Optimization and support

Post-launch, we monitor AI solution performance, gather user feedback, and continuously improve. Regular updates keep models current, optimize costs, and add new features. Ongoing support ensures your AI investment delivers lasting value.

How much does AI development for Drupal cost?

Every project is scoped after the free consultation. Cost depends on use cases, content volume, cloud APIs or on-premise LLMs, and ongoing support.

Every project includes: discovery workshop, technical documentation, production deployment and testing, post-launch support, and knowledge transfer for your team.

AI models and technology

  • Cloud APIs such as OpenAI, Anthropic and Gemini — usage-based pricing.
  • Open-source LLMs (Llama, Mistral) — hosting and ops, no API fees.
  • On-premise models when content cannot leave your network.

Development scope

  • Focused MVP: one chatbot or one editorial workflow.
  • Integration with your Drupal content model, permissions and review queues.
  • Enterprise scope with custom agents, governance and monitoring.

Ongoing investment

  • API traffic and model usage for cloud setups.
  • Hosting and maintenance for on-premise models.
  • Support, tuning and editor onboarding after launch.

Ready to add AI to your Drupal site?

Talk to our team. We will tell you what is realistic, what it costs and where to start.

Book a free consultation

AI for your Drupal site, or AI for your whole company?

This page covers AI inside Drupal. If you want company-wide AI agents, internal knowledge assistants, n8n workflows or on-premise LLM operations, see droptica.ai.

Frequently asked questions

We answer this during the free consultation based on your Drupal version, content model, data boundaries and priority use case.

We answer this during the free consultation based on your Drupal version, content model, data boundaries and priority use case.

We answer this during the free consultation based on your Drupal version, content model, data boundaries and priority use case.

We answer this during the free consultation based on your Drupal version, content model, data boundaries and priority use case.

We answer this during the free consultation based on your Drupal version, content model, data boundaries and priority use case.

We answer this during the free consultation based on your Drupal version, content model, data boundaries and priority use case.

We answer this during the free consultation based on your Drupal version, content model, data boundaries and priority use case.

We answer this during the free consultation based on your Drupal version, content model, data boundaries and priority use case.

We provide ongoing support, monitoring, and optimization. Track AI adoption metrics, model performance, API costs. Regular updates ensure generative AI software development evolves with your needs. Support packages available tailored to your specific needs and project scope.

We define success metrics during discovery: time saved (hours → minutes), cost reduction (support tickets, manual work), revenue increase (conversion rates, upsells). Track before/after metrics, analyze AI solution impact, provide quarterly reports with actionable insights.

Tell us about your Drupal site and what you want AI to do

We narrow down scope and give you a realistic estimate faster when you include your Drupal version, the content bottleneck you want to solve first, data residency limits, timeline and budget range.

After you submit: we review your message and reply with questions or a proposed consultation call.