Automation

AI Agents and Workflow Automation

Stop copy-pasting between 11 SaaS tabs. Automate the workflow that eats your team's week.

AI Agents and Workflow Automation

AI agents and automated workflows, built to run in production

Most companies bought 30 SaaS tools and stitched them together with two Zaps and a prayer. The result: people spend hours every day moving information between tabs. Copying a status from project management to the CRM. Updating billing from support tickets. Pulling reports from one tool into another. AI agents (smart software that can read, decide, and take action) plus modern workflow tools (n8n, Make, Temporal, or custom code) cut that work from hours to seconds. A first workflow often removes hours of manual copy-paste from your team's week.

This is project work, not a platform you subscribe to. We build the specific agents your team needs, in the tools you already use, with your data. Then we keep them running.

When to talk to us

  • Your team is stuck doing high-volume repetitive work (operations, sales, customer success, finance, HR) and your Zapier or Make setup is hitting its limits.
  • You tried to build AI agents in-house and ran into a maintenance nightmare.
  • You need agents that do real work (make decisions, take actions, escalate to humans when needed), not chatbots that just answer questions.
  • You're moving off Zapier or Make to something more powerful and want expert advice before you commit.
  • You have workflows that cost real money in human time. Common examples: invoice processing, lead enrichment, customer support triage, compliance review, contract redlining.

What you get

A typical project covers 1 to 4 specific high-value workflows.

Project scope ($25,000 to $150,000, 4 to 12 weeks):

  • Workflow audit. We find the 1 to 4 highest-value tasks your team does over and over.
  • Architecture design. Which tools to use (n8n, Make, Temporal, or custom code). What each agent is allowed to do. How we'll see what they're doing. What happens when something breaks.
  • Build. Full implementation in your environment. Code lives in your repo or your n8n/Make account, never ours.
  • Integrations. CRM, support tools, billing, internal databases, Slack, email, chat.
  • Human-in-the-loop fallback. When the agent isn't sure, a human reviews. The agent never takes actions you can't undo without your team's approval.
  • Logs you can audit. Every action logged. Every decision traceable. Every prompt versioned. You can replay anything, anytime.
  • Acceptance test. We run 100 sample inputs and measure success. We agree the target before we start (usually 85 to 95 percent, depending on the workflow). If we miss it, we rebuild on our dime.

Ongoing maintenance ($2,500 to $7,500 per month):

  • Monthly health check. How well the agents are doing, what's drifting, what's breaking.
  • Tuning prompts and workflows as your business changes.
  • Support when AI vendors release new models or break old ones.
  • 4 hours per month of architecture and roadmap time.

Guarantee

Every agent has to hit its agreed success rate on 100 real sample inputs before we send the final invoice. If it doesn't, we rebuild on our dime. The test is written in the contract and run with you watching. No closed-door pass-fail decisions.

Single workflow ($25,000 to $50,000, 4 to 6 weeks)

For one high-value task your team does over and over. Examples: invoice processing, lead routing, support ticket triage, compliance review of one document type.

What's included:

  • Discovery session (2 hours) and written process map of the task as it works today.
  • Architecture document. Which tool we'll use (n8n, Make, Temporal, or custom code), why, and how it fits your stack.
  • Up to 8 system integrations (CRM, email, Slack, billing tool, internal database, etc.).
  • Up to 3 AI decision points in the workflow (e.g., classify intent, pick a route, escalate to human).
  • Logging dashboard so you can audit what the agent did and why.
  • Acceptance test on 100 of YOUR real sample inputs.
  • 2 weeks of post-launch tuning included.
  • Source code in your repo. You own everything.

Multi-workflow ($50,000 to $100,000, 6 to 10 weeks)

For 2 to 3 connected workflows where the output of one becomes the input of another. Example: inbound lead → enrichment → routing → first-touch outreach.

Everything in Single workflow, plus:

  • 2 to 3 workflows that share state and pass data between each other.
  • Up to 15 system integrations.
  • Up to 8 AI decision points across the workflows.
  • Cross-workflow observability (you see the full journey, not just one step).
  • Workflow-level error handling and retry logic.
  • 4 weeks of post-launch tuning included.

Department-wide ($100,000 to $150,000, 10 to 12 weeks)

For 4 or more workflows that cover one department end-to-end. Example: all of customer support, all of accounts payable, all of sales operations.

Everything in Multi-workflow, plus:

  • 4 or more workflows for one department.
  • Up to 25 system integrations.
  • Up to 15 AI decision points.
  • Department-level dashboard (manager view of how all agents are performing).
  • Custom alerts for your team when agents need human review.
  • Training session for the department on what to expect and how to give feedback.
  • 6 weeks of post-launch tuning included.

Ongoing maintenance ($2,500 to $7,500 per month)

Optional, not required. Your team can run its own maintenance after handoff.

What's included:

  • Monthly health check report. Success rate, drift, error patterns, what's degrading.
  • Up to 4 hours of prompt and workflow tuning per month.
  • Vendor and model upgrade support (when OpenAI releases a new model, when n8n breaks a connector).
  • Same-week response when something stops working.
  • 1-hour quarterly architecture review.

Payment terms

50 percent on contract signing. 25 percent at midpoint. 25 percent on acceptance. INR pricing on request for India-based clients.

Selected work

A few automations we have built to demonstrate the approach:

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Not sure if this is the right page? This is for multi-step processes that move work between tools and systems. If your problem is high-volume documents arriving and needing to be read, extracted and routed, start at AI Document Processing.

Frequently Asked Questions

Why pay you when n8n and Make are no-code?+
No-code tools are great for simple connections (move data from A to B). They struggle when you need: decisions that require AI judgment, recovery when something fails in a way you can't undo, tracking what hundreds of agent runs did across a day, multi-step decisions across systems, and integrations with your custom internal tools. The tools are the easy part. The hard part is designing the agents, writing the prompts, and building the safety nets. That's what we do.
Which workflow tool do you recommend?+
It depends on what the workflow needs to do. We default to n8n for connecting tools and moving data (cheap, fast, you can host it yourself, big library of pre-built integrations). Make works when your team prefers a visual drag-and-drop editor. Temporal is the right choice for long workflows where reliability matters (financial close, multi-step compliance, anything that can't fail halfway through). Custom code when the workflow is core to your business and you don't want vendor lock-in. We pick per workflow, not per company.
What about LangChain, LangGraph, or CrewAI?+
We use them where they fit, but we don't bet your business on any one of them. AI frameworks change fast. We write the code so the framework can be swapped out later without a full rebuild. Your real investment is in the prompts, the tools the agents can use, and the logging. Those last.
What if the agent does something it shouldn't?+
Three layers of safety: (1) anything that can't be undone (deleting data, making a payment, sending a public message) requires human approval first, (2) new agent versions run in test mode before going live, (3) we log every action so we can replay and fix any mistake. We never ship agents to production without all three in place.
What is a typical ROI?+
It depends on the workflow. A common pattern: invoice processing that used to take 40 hours a month per accountant drops to 4 hours of review. That's $60,000 to $90,000 a year saved per accountant whose time is freed up. Most projects pay for themselves in 6 to 12 months. We run the actual math on your specific workflows in the proposal, not a generic estimate.
AI Agents
Workflow Automation
n8n
Temporal

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