?php
return [
    'meta.ai-workflow.title'       => 'Workflow Automation Agency',
    'meta.ai-workflow.description' => 'Workflow automation agency building LLM-augmented workflows — natural language processing, document extraction, intelligent routing, and exception handling beyond what Zapier can do.',

    'ai-workflow.hero.eyebrow' => '[ AI AUTOMATION ]',
    'ai-workflow.hero.h1'      => 'Workflow Automation Agency',
    'ai-workflow.hero.sub'     => 'Point-and-click automation tools handle simple trigger-action sequences. We build LLM-augmented workflows that process natural language inputs, extract structured data from documents, route work intelligently based on context, and handle exceptions that would break a rule-based system.',
    'ai-workflow.parent'       => 'AI Automation Agency',

    'ai-workflow.diff.h2' => 'LLM-Augmented Workflows, Not Just Zapier',
    'ai-workflow.diff.p1' => 'Zapier, Make, and Power Automate are excellent for connecting structured data between SaaS tools. They fall apart when the input is a PDF, an email, a form with free-text fields, or a decision that requires understanding context. We build workflows that use LLMs at the points where structure ends: extracting fields from documents, classifying unstructured inputs, generating responses, and routing based on intent rather than keywords.',
    'ai-workflow.diff.p2' => 'Every workflow we build includes explicit exception handling — what happens when the LLM is uncertain, when a document is illegible, when a required field is missing. Exceptions are surfaced to a human with full context, not silently dropped or incorrectly processed. Your team sees only what needs a decision; the volume work runs autonomously.',

    'ai-workflow.inc.label'                      => 'WHAT\'S INCLUDED',
    'ai-workflow.inc.h2'                         => 'Workflow Automation Services',
    'ai-workflow.inc.llm-workflows.h3'           => 'LLM-Augmented Workflow Design',
    'ai-workflow.inc.llm-workflows.p'            => 'We design and build workflows where LLMs handle the steps that require language understanding: classifying inputs, extracting structured data, generating responses, and making routing decisions. The LLM operates within defined guardrails with fallback to human review when confidence is low.',
    'ai-workflow.inc.integrations.h3'            => 'System Integrations',
    'ai-workflow.inc.integrations.p'             => 'We connect your workflow to the systems it needs: CRMs, ERPs, ticketing systems, document stores, email, Slack, and custom APIs. Integrations are built at the API layer — stable, maintainable, and not dependent on UI scraping or brittle connectors.',
    'ai-workflow.inc.document-processing.h3'     => 'Document Processing & Extraction',
    'ai-workflow.inc.document-processing.p'      => 'Invoices, contracts, onboarding forms, compliance documents — we build extraction pipelines that pull structured fields from unstructured documents using LLMs with validation logic. Output lands directly in your target system, flagging exceptions for human review.',
    'ai-workflow.inc.monitoring.h3'              => 'Monitoring & Reliability',
    'ai-workflow.inc.monitoring.p'               => 'Every workflow runs with observability: throughput metrics, exception rates, LLM decision logs, and latency tracking. We review weekly post-launch, tune prompts and routing logic as your inputs evolve, and alert on anomalies before they become problems.',

    'ai-workflow.faq.h2' => 'Frequently asked questions',
    'ai-workflow.faq.q1' => 'What’s the difference between workflow automation and process automation?',
    'ai-workflow.faq.a1' => 'The terms are often used interchangeably, but workflow automation typically refers to automating sequences of tasks within a defined process — routing a document through approval steps, triggering notifications, updating records. Process automation is broader: it encompasses redesigning the whole process, not just digitising the existing steps. We do both, but we always start with understanding the process before designing the automation.',
    'ai-workflow.faq.q2' => 'What tools do you use for workflow automation?',
    'ai-workflow.faq.a2' => 'We select tools based on what the workflow requires. For orchestration: LangChain, LlamaIndex, Temporal, or custom Python depending on complexity. For integrations: REST APIs, webhooks, and official SDKs — not screen scrapers. For simple trigger-action steps where it fits, we use n8n or Make. We avoid locking you into a single vendor’s platform. All code goes into your repository.',
    'ai-workflow.faq.q3' => 'How is LLM-powered automation different from traditional workflow automation?',
    'ai-workflow.faq.a3' => 'Traditional workflow automation requires every input to be structured and every decision to be expressible as an explicit rule. LLM-powered automation handles unstructured inputs (emails, PDFs, free text), makes decisions based on context rather than keywords, and adapts to variation without breaking. The trade-off is that LLM steps require monitoring and prompt maintenance — they’re not set-and-forget. We build the observability layer that makes them manageable.',
    'ai-workflow.faq.q4' => 'What types of workflows are best suited for automation?',
    'ai-workflow.faq.a4' => 'High-volume, repeatable workflows where the inputs vary but the overall structure is consistent. Best candidates: document intake and data extraction (invoices, contracts, applications), customer request triage and routing, internal approval and sign-off chains, data synchronisation between systems, and report generation from structured data sources. If a workflow currently requires a human to read something and decide what to do next, it’s worth assessing for automation.',

    'ai-workflow.cta.h2'  => 'Tell us about the workflow you want to automate',
    'ai-workflow.cta.sub' => 'Describe the inputs, the decisions, and the outputs. We’ll assess what’s automatable, where LLMs add value over rules, and what a realistic build looks like.',
];
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