H
    Hestur
    Platform / n8n

    n8n Automation
    Agency

    We build, deploy, and maintain n8n workflows for businesses that want data sovereignty, AI-native automation, and no per-operation pricing. Simple flows in 1–2 weeks. Complex multi-system builds in 4–8 weeks.

    Self-hosted or CloudCustom JS nodesAI-native workflowsMCP integration

    Real Client Result

    $180K/year saved — SaaS contract renewal automation

    A UK-based B2B SaaS company had 3 FTEs spending 60% of their time manually processing 4,000 monthly contract renewals — pulling from HubSpot, checking entitlements, drafting emails, and updating records. Each renewal took 8–12 minutes of human time.

    We built a self-hosted n8n workflow: triggers on deal stage change in HubSpot → retrieves contract details via API → passes to Claude Sonnet to generate a personalised renewal summary and email → sends via SendGrid → writes reply tracking back to HubSpot → escalates non-responses at day 7 and 14. Deployed in 11 days.

    11 days
    to deploy
    3 FTEs
    reallocated
    $180K
    annual saving
    98%
    renewals processed on time
    What We Build

    Six n8n Workflow Categories

    CRM & Sales Pipeline Automation

    Lead enrichment, qualification scoring, follow-up sequences, and deal stage transitions — all triggered by real events in HubSpot, Salesforce, or Pipedrive. No manual data entry. No missed follow-ups.

    Lead scoring, SDR sequences, deal close triggers

    AI-Native Document Processing

    Ingest PDFs, contracts, invoices, or reports via n8n HTTP triggers. Pass to Claude or GPT-4o for extraction, classification, or summarisation. Write structured output back to your database or CRM.

    Contract review, invoice extraction, report summarisation

    Multi-System Data Synchronisation

    Keep ERP, CRM, accounting, and operations tools in sync without expensive iPaaS connectors. n8n runs on your infra, respects your data boundaries, and handles the mapping logic you need.

    Shopify → Xero, HubSpot → Netsuite, Jira → Slack

    Customer Onboarding Workflows

    Trigger multi-step onboarding sequences when a deal closes: provision accounts, send welcome sequences, assign CSMs, create onboarding tasks, and schedule kickoff calls — automatically.

    SaaS onboarding, client intake, access provisioning

    AI Agent Tool Backends

    n8n workflows act as callable tools for LLM agents — a Claude or GPT-4o agent calls your n8n webhook mid-conversation to look up data, create records, or trigger business actions. MCP integration included.

    CRM lookups, booking creation, data retrieval

    Operations & Reporting Automation

    Daily KPI reports, anomaly detection alerts, SLA breach notifications, and executive summaries generated automatically and delivered to Slack, email, or your BI tool.

    Weekly revenue reports, SLA alerts, ops dashboards

    Deployment Decision

    Self-Hosted vs n8n Cloud

    Both are valid. The decision comes down to data sovereignty, volume, and team capacity.

    Attributen8n CloudSelf-Hosted
    Cost at 100k executions/month~$50/month$20–40/month (server)
    Data stays on your infrastructureNoYes
    HIPAA / SOC 2 alignmentLimitedYou control it
    Maintenance overheadZeroLow (Docker/K8s)
    Setup time<1 hour2–4 hours
    Custom node installationRestrictedFull access
    Queue mode + workersManagedRedis + multiple workers
    Horizontal scalingAutoManual or Kubernetes HPA
    Our default recommendation: Start with n8n Cloud if you are building quickly and your data can leave your infra. Move to self-hosted when you hit 100k+ executions/month, have strict data residency requirements, or need custom node packages.
    AI Integration

    AI-Native Workflows
    & MCP Integration

    LLM Nodes in Production

    HTTP Request → OpenAI / Claude

    Any LLM can be called via n8n's HTTP Request node. We use structured output schemas (JSON mode) so LLM responses are machine-readable and flow directly into downstream nodes without parsing.

    Native AI Agent node

    n8n's built-in AI Agent node supports tool calling with LangChain under the hood. Agents can call other n8n nodes as tools — lookup, create record, send notification — all within one workflow.

    Document processing pipelines

    PDF or image → Extract Text node → LLM for classification/extraction → structured output → database write. We handle multi-page documents, mixed formats, and high-volume batch processing.

    Memory across sessions

    Persistent memory using Redis or Postgres vector store nodes. Agents remember previous interactions with a contact — critical for customer service and relationship-driven workflows.

    MCP Server Integration

    n8n as MCP tool — Claude calls your workflow

    Claude agent: "Get the latest order status"

    → MCP tool call: get_order_status

    { orderId: 'ORD-4829' }

    → n8n webhook triggers

    Queries Shopify API

    → Returns structured JSON to Claude

    → Claude: "Order #4829 is in transit..."

    We build n8n as an MCP server — every workflow becomes a callable tool for Claude, ChatGPT, or your custom agent.
    Works with any LLM that supports tool calling (OpenAI function calling, Anthropic tool use, LangChain tools).
    Allows AI agents to trigger business actions — create CRM records, send emails, query databases — without direct API access from the LLM.
    We write the MCP schema, webhook handler, and authentication layer so your workflows are securely callable.
    Custom Development

    Custom Node Development

    When n8n does not have a native integration for your tool, we write it in TypeScript.

    Proprietary API nodes

    Your internal APIs, legacy systems, and niche SaaS tools without community nodes. We build the node, write the credential schema, and publish it to your self-hosted instance.

    Complex transform nodes

    Heavy data transformations that exceed what the Code node handles cleanly. Custom nodes with full TypeScript, unit tests, and proper error handling.

    Performance-critical nodes

    Nodes processing large datasets (10k+ records per execution) benefit from optimised TypeScript with streaming, batching, and memory management built in.

    What We Solve

    5 n8n Failure Modes
    We Fix Before They Hit Production

    01

    Problem

    Workflows that crash silently

    Impact

    n8n workflow errors do not always send notifications by default. A broken workflow can silently drop data for days before anyone notices — by which point the downstream damage is significant.

    Our Fix

    We add error trigger nodes to every critical workflow, route failures to a dedicated Slack channel with workflow name, execution ID, and failed node. Critical workflows get PagerDuty alerts.

    02

    Problem

    Unthrottled API calls

    Impact

    n8n's default behaviour is to execute nodes as fast as possible. On a bulk operation (10,000 records), this saturates downstream APIs, triggers rate limits, and causes partial failures that are hard to recover.

    Our Fix

    We add batch sizing (typically 100–200 records), inter-batch delays matched to target API rate limits, and idempotency keys so retries do not create duplicate records.

    03

    Problem

    No execution history retention policy

    Impact

    n8n stores every execution log in its database. A high-volume workflow with no pruning policy inflates the database to gigabytes within weeks, degrading performance.

    Our Fix

    We configure execution data pruning (typically 14–30 days for non-error executions, 90 days for errors), set up automated database backups, and monitor database size with alerting.

    04

    Problem

    Credentials stored insecurely

    Impact

    Teams sometimes hardcode API keys in workflow nodes instead of using n8n's credential store. Keys in workflow JSON are visible to anyone with workflow access and get exported in workflow backups.

    Our Fix

    All secrets go through n8n's encrypted credential store. We audit all workflows before go-live to confirm zero hardcoded credentials, and set up credential rotation reminders.

    05

    Problem

    Single-worker bottleneck under load

    Impact

    A default n8n setup uses one main process. A spike in concurrent workflows queues behind a long-running execution, causing delays across unrelated workflows.

    Our Fix

    For workloads above 50 concurrent executions, we deploy n8n in queue mode — a Redis queue, a main process for webhooks, and N worker processes. Workers scale horizontally as load increases.

    Timeline

    How Long Does It Take?

    1–2 weeks

    Simple Workflows

    Single-system integrations, linear trigger → action flows, data sync between two tools.

    • Requirement mapping (1 session)
    • Build + test in staging
    • Error handling and monitoring
    • Handoff with documentation
    4–8 weeks

    Complex Multi-System Builds

    Multi-system orchestration, AI nodes, custom node development, queue mode setup.

    • Architecture design + data flow mapping
    • Custom node development (if needed)
    • Staged build: core flow → integrations → AI layer
    • Load testing, error hardening, monitoring
    Start Automating

    Ship Your First n8n Workflow
    in Under 2 Weeks

    Tell us what you want to automate. We scope it in 30 minutes, build it in 1–8 weeks, and hand it off fully documented.