AI automation services
AI Agent & Automation Sprint for one repetitive business workflow.
I build one AI automation around one recurring task: AI customer service, lead follow-up, support triage, document intake, reporting, CRM cleanup, or similar. Not a generic chatbot. Not a prompt pack. A small working system connected to your tools with review points where accuracy matters.
We pick one repeatable task, define good output with real examples, connect the tools, and ship a first AI automation with review points where accuracy matters. The sprint stays focused on one business workflow, not an agent that tries to do everything.
Good fit
Use AI automation when the workflow is already repeatable.
- You have leads, support tickets, documents, reports, or CRM work piling up every week.
- The task is repetitive, but still needs judgment and context.
- You can share tool access, real examples, and one decision-maker during the sprint.
Bad fit
Avoid this sprint when the request is vague or access is missing.
- You want one agent to run your whole company.
- You do not have access to the data or tools the agent needs.
- You need a no-code toy instead of something built around your workflow.
Workflows this sprint is built to handle.
AI customer service agent
Triage support tickets, draft replies, classify issues, and route exceptions so customers get a faster first response without removing human review.
Lead follow-up automation
Qualify inbound leads, enrich context, draft replies, update the CRM, and alert the right person before a warm lead goes cold.
Document intake agent
Parse forms, PDFs, emails, invoices, or applications into structured records with confidence checks and a review surface.
CRM cleanup and reporting
Turn messy notes, spreadsheets, and activity logs into cleaner CRM fields, weekly summaries, and exception reports.
What you get by day five.
Scope from real examples
A short map of the job, the inputs, the expected outputs, the edge cases, and where a human should review.
Custom agent
The AI agent logic, prompts, tools, guardrails, and edge-case handling for the one workflow we choose.
Tool integrations
Connections to the systems needed for the job: CRM, email, Slack, forms, sheets, ecommerce tools, database, or APIs.
Dashboard or review surface
A small interface so you can see what the agent did, approve sensitive actions, and catch mistakes before they matter.
Monitoring and handoff
Basic logs, alerting, operating notes, and a Loom walkthrough so you are not dependent on memory.
A five-day path from examples to a working automation.
Pick the job and examples
We choose one workflow and define what “working” means using real inputs, outputs, and edge cases. This is where we keep the sprint honest.
Connect the inputs
I set up the repo, data shape, tool access, and first agent loop.
Build and test
I build the agent, test real examples, add review points, and send you short Loom updates.
Launch the first version
We deploy it, walk through the system, and decide what should move into the monthly retainer.
Working against agreed examples by day 5, or I keep building.
If the scoped workflow is not working against the agreed examples by the end of the sprint, I keep working on it at no extra charge until it does. The guarantee applies to the agreed scope, provided access and feedback arrive on time.
Agent tools are chosen around your workflow and review needs.
Relevant proof from shipped backend, automation, and data systems.
Ejaz is a great and experienced engineer, and I would hire him again in an instant. His communication skills are good, he is flexible, has a lot of all round experience.
Great quality work, comprehensive, and thorough.
Questions to answer before booking an AI automation sprint.
Is this AI automation services or AI agent development?
Both terms describe the same buyer need, but the implementation is workflow-first. I build an AI agent only where it helps a specific business process produce a better output faster.
Will this replace a person?
Sometimes it replaces part of a role. More often, it removes the boring first pass so a person can review, decide, and handle exceptions faster.
Can the agent take actions automatically?
Only where it is safe. For risky actions, I add human review. The goal is useful automation, not reckless autonomy.
What does the monthly retainer cover?
Hosting help, model changes, prompt tuning, monitoring, a monthly health check, and small workflow edits. Response window and cancellation terms are agreed before the retainer starts.