Draft & Goal

What Draft & Goal does

Draft & Goal is a multi-agent orchestration platform for enterprise marketing. It runs recurring marketing work from research and production to localization, QA, publishing, and reporting. The platform connects marketing tools into one operating flow, enabling teams to scale marketing processes, make rules operational, and improve playbooks. It is designed to give enterprise marketing teams a platform to compose autonomous agents, run them safely at scale, and trust the results. The platform is model-agnostic, cloud-agnostic, and built for production-grade execution with observability, recoverability, and auditability.

Products

• Draft & Goal MarketingOSA multi-agent orchestration platform for enterprise marketing that automates recurring work from research and production to localization, QA, publishing, and reporting.
• StudioA visual canvas for building agentic workflows with drag-and-drop functionality, variables, conditionals, loops, and human-in-the-loop nodes. It includes 80+ pre-built nodes for AI, integrations, tools, and I/O.
• AgentsAutonomous agents that reason, act, and collaborate. The AI Agent node is a reasoning runtime that plans, decides, calls tools, and adapts. Multi-agent teams can share memory and hand off context.
• OrchestratorA production-grade execution engine that runs thousands of workflow instances in parallel with retries, quotas, and resumable runs, designed for multi-cloud environments.
• ConnectorsA library of 30+ enterprise integrations, plus open escape hatches like the API Connector for any REST endpoint, the Web Scraper for any page, and MCP for any server.
• Workflow GeneratorA tool that builds complete, editable workflows from a natural language description, wiring nodes, configuring AI, and generating validated code.

Key capabilities

• Agentic marketing platform
• Multi-agent orchestration
• Visual workflow building (Studio)
• Autonomous AI agents with reasoning runtime
• Production-grade execution (Orchestrator)
• 30+ enterprise integrations and custom connectivity (Connectors)
• Model-agnostic by default (supports Claude, Gemini, GPT, Llama, Mistral)
• Cloud-agnostic (GCP, AWS, OVHcloud, on-premise options)
• Human-in-the-loop approval checkpoints
• Automated cross-channel reporting
• AI-generated executive summaries with anomaly callouts
• Site-wide content audits with AI quality scoring
• Keyword research at scale
• Internal linking optimization with semantic recommendations
• Programmatic SEO for generating and refreshing pages
• Content repurposing (article to LinkedIn carousel, etc.)
• Image & video generation (via Imagen, Veo, Sora)
• Lead sourcing, enrichment, and personalization
• CRM write-back (HubSpot, Salesforce)
• Real-time monitoring and 90-day run history
• Scheduling, batch runs, and API access
• Private data sources and webhooks
• Drafts, versioning, and team roles
• SSO / SAML and fine-grained permissions
• Audit trails and custom retention
• Private models, VPC, or on-prem options
• Workflow generator from natural language prompts
• Typed, compatibility-checked connections between nodes
• Anti-pattern detection in workflow generation
• Role-based access control
• Data encryption in transit and at rest
• Data isolation per organization

Use cases

• SEO at enterprise scale (audit, optimize, publish across millions of pages)
• Content production (from brief to publish with brand voice intact)
• Lead generation (source, enrich, personalize, convert prospects)
• Marketing analytics (reporting that explains itself)
• Blog & article production
• Brand consistency at scale
• Governance, compliance & audit for content
• Content refresh & optimization
• Content cost reduction
• Editorial planning & workflows
• Localization & translation
• Site & content migration
• Product & category pages at catalog scale
• Scaled SEO content production
• Turn search opportunity into market-ready content
• Keep campaigns moving from plan to launch
• Build qualified pipeline without manual research
• Scrape, enrich, and log data end-to-end
• Warehouse analytics (query BigQuery, reason over rows, write digest to Sheets)
• Search reporting (pull Search Console rows, find decaying queries, log automatically)
• Driving any internal API through API Connector or MCP server

AI approach

Draft & Goal is an agentic marketing platform that uses autonomous AI agents to automate marketing workflows. It emphasizes a model-agnostic approach, allowing users to choose and swap between various large language models (LLMs) like Claude, Gemini, GPT, Llama, and Mistral, routed via different cloud providers (Vertex, Bedrock, OpenAI, Anthropic, OVHcloud). The platform provides a visual canvas (Studio) for building workflows with pre-built nodes, including AI Agent nodes that act as reasoning runtimes, planning, calling tools, and adapting to achieve goals. It supports multi-agent teams that collaborate and share memory. The platform is designed for production-grade execution, auditability, and compliance, with a focus on human-in-the-loop approvals.

Tech named: AI Agent node, Multi-agent teams, LLM node, RAG datasources, MCP servers, GPT-4, Claude Sonnet, Claude Opus, Gemini Pro, Imagen, Veo, Sora, Vertex, Bedrock, OpenAI, Anthropic, OVHcloud, Llama, Mistral

Industries served

• Energy & utilities
• Financial services & insurance
• Healthcare & pharma
• Manufacturing & industrial
• Professional & B2B services
• Public sector & government
• Retail & e-commerce
• Technology & SaaS
• Telecom & media
• Travel & hospitality
• Marketplace

What it says sets it apart

• Agentic AI changes the unit of work from tasks people do to outcomes agents own.
• Focus on agents, not assistants, meaning agents own outcomes and drive decisions.
• Model-agnostic by default, supporting multiple LLM providers (Claude, Gemini, GPT, Llama, Mistral) and allowing switching with one config change.
• Production from day one, with a system designed for observability, recoverability, and auditability.
• Orchestration layer for enterprise marketing, connecting steps from signal and decision to production, approval, publishing, measurement, and back again.
• Ability to scale without drift, making best marketing processes the default and operationalizing brand/compliance rules.
• Four layers of architecture (Studio, Agents, Orchestrator, Connectors) that compose together for efficiency.
• Visual canvas with engineering rigor, allowing marketing ops to design and engineering to review.
• AI Agent node is a true reasoning runtime, not just an LLM wrapper, capable of planning, tool calling, and adapting.
• MCP-native, allowing agents to be extended with internal systems (data warehouse, CMS, brand guidelines, CRM) without custom integration.
• Workflow Generator that builds complete, editable workflows from natural language descriptions, including typed connections and validated code.
• Transparent workflow generation process, showing agent's reasoning stream live.
• Comprehensive trust and compliance features (SOC 2 Type 1, ISO 27001, GDPR, EU AI Act alignment, SSO/SCIM, data residency, encryption, access control, data isolation, human-in-the-loop, vendor review, incident response).