Basic chatbot
- ×Replies to typed questions
- ×Has no access to your systems
- ×Cannot act on your behalf
- ×No connection to your tools
- ×Needs a person to move work forward
Services
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AI Automation for Business Operations
We build AI workflow automation into the operational work your team already does. It connects to your real systems, stays inside clear limits on what it can do, and keeps a person in control where it matters. The result is less manual work you can actually rely on.
- $4,500
- AI Readiness Review: which process to automate first, fixed price, 3 weeks
- $12,000
- Guide price of a first workflow in production, 3–5 weeks
- 4
- Open-source MCP servers and Claude plugins we publish
What we automate
Business process automation with AI works best one process at a time. Pick one process first. Build around that.
Document processing
PDFs, forms and invoices turned into checked data before anything is saved. At Get Energy, supplier price sheets are parsed by AI and verified by a person, with up to 75% less manual preparation per import.
Customer and vendor requests
Repeat questions answered from your own data, replies drafted for a person to send, unclear cases handed to the right person. On a procurement platform, an agent chases missing vendor documents while sensitive actions wait for approval.
Internal knowledge
Policies, SOPs and internal documents answered in plain language for the employees who ask the same questions every week.
Reports and summaries
Updates, summaries and change flags prepared from your systems and saved inside them. In the Get Energy ERP, summaries are up to 85% faster than rebuilding a client's context by hand.
Sales follow-up
Lead checks, reply drafts and CRM notes, so the team follows up faster without retyping.
Approvals and multi-step workflows
Approvals, tool handoffs and multi-step processes built around how your team already works.
Need an agent that takes actions on its own, inside limits you set? See AI Agent Development. Not sure which process to start with? The AI Readiness Review picks it in three weeks.
A chatbot answers. A workflow does the work.
A chatbot replies to questions. A real workflow does the work: it reads your systems, acts inside limits you set, routes what needs a person, and writes results back where your team works.
AI workflow in your operations
- Works from your approved business data
- Acts inside permissions you set
- Connects to your existing tools
- Routes cases to the right person
- Writes results back where your team works
See how these workflows run in production
Real AI workflows, with the constraints, control, and delivery behind them.
Thin slice to productionOne supplier price import narrowed to a first production slice, with acceptance criteria and a person's review before anything reached live pricing. Up to 75% less manual preparation per import.Read the caseConfidential clientAgentic workflow with guardrailsVendor onboarding where the agent drafts and reminds, sensitive actions still need a person's approval, and a rollback path exists. Up to 40% faster early onboarding.Read the caseAI summaries inside the ERPSummaries saved inside the ERP with a freshness check and settings the admins control. AI working inside an existing system of record, not beside it. Up to 85% faster context reconstruction.Read the caseObservability and incident responseOur own production system. What happens after launch, when live behaviour drifts: the signals worth watching, and who answers when quality moves.Read the caseStart with one process that costs time
Bring a task, department, or problem. We help decide where AI can save time first.
- Find the time drain
We look for work your employees repeat every week.
- See where the work happens
We check the tools, files, emails, and systems your business already uses.
- Keep people in control
We decide what AI can handle and what should go to a person.
- Build a small working version
We create the first AI setup around one real business task.
- Try it with real employees
Your staff tests it on real questions, documents, or requests.
- Improve what people actually use
We fix weak spots and expand only when the first version is useful.
Where this works
AI works best when the task repeats often and follows a clear process.
Manufacturing
AI automation for manufacturing can help with supplier emails, production reports, quality documents, inventory questions, and order status.
Logistics
AI automation for logistics can help with shipment updates, delivery exceptions, document checks, dispatch support, and customer messages.
eCommerce
AI automation for eCommerce can help with order questions, returns, product information, customer support, and inventory updates.
Healthcare
AI automation for healthcare operations can help with patient FAQs, appointment routing, admin documents, internal knowledge, and sensitive case handoff.
Finance
AI automation for finance and insurance can help with document intake, policy questions, claim summaries, case routing, and internal compliance knowledge.
Real Estate
AI automation for real estate can help with lead checks, property questions, document collection, appointment follow-ups, and CRM updates.
Legal
AI automation for legal and accounting teams can help with client intake, document summaries, deadline tracking, structured data extraction, and internal knowledge.
B2B Services
AI automation for B2B services can help with proposal drafts, meeting summaries, client follow-ups, internal reporting, and knowledge search.
Control and data stay in your hands
We keep each workflow clear, limited, and reviewable. You decide what the AI can access, what stays private, and where a person signs off.
Human approval: Sensitive actions wait for a person.
Limited access: AI only gets the access it needs for this workflow.
Clear handoff: Unclear cases go to the right person.
Full logs: You can see what the AI accessed, acted on, or changed.
Defined outcome: We set what success looks like before we build.
Data rights: We define what data AI can use, what stays private, and who owns the output.
Who leads your project
Three people with clear roles: one accountable for our AI work as a whole, one who leads the build, and one who leads the process and your side of the conversation.
Heads our AI work
Accountable for how we do AI work across every project.
Leads the AI development
Leads the build of your agent, from the first path to the release.
Leads the process and the client side
Leads the communication with you, the process and the specification.
Built by engineers, not prompt templates.
AI automation works better when it is built by people who understand real business processes and can turn them into working software.
Lazy Ants brings AI engineering, product thinking, and delivery experience into practical systems your employees can actually use.
Partner Network
- Lazy Ants is part of the Claude Partner Network, Anthropic's partner program for organizations helping businesses adopt Claude.
Skilled AI engineering team
- We build AI automation with engineering discipline: integrations, permissions, data flow, testing, deployment, and post-launch support.
MCP servers and tooling we've built
Follow our AI open-source projects and see how we build practical AI infrastructure, MCP servers, and Claude tooling.
Where to start
Not sure which process to automate first? Start here
The review picks the process, measures what it costs today and tells you whether it is ready, before anything is built.
Questions we get before booking
If yours is not here, ask on the first call. We would rather tell you AI is the wrong tool for a process than sell you a build.
What can AI automate in a business?
Work that repeats and follows a clear process: document processing, answers to repeat requests from your own data, internal knowledge search, reports and summaries, sales follow-up and approvals. We start with one process and widen it after it has held up in real use.
What is the difference between an AI chatbot and AI workflow automation?
A chatbot replies to typed questions. A workflow does the work: it reads your systems, acts inside limits you set, routes what needs a person, and writes results back where your team works.
Do we have to replace our tools?
No. The automation works with the tools, files, emails and systems your business already uses, and writes results back where your team works.
What stays under human control?
Sensitive actions wait for a person's approval, the AI gets only the access the workflow needs, and unclear cases go to the right person. Every action is logged, so you can see what the AI accessed, acted on or changed. You decide where a person signs off.
How much does it cost, and how long does it take?
The AI Readiness Review is $4,500, fixed, and takes three weeks. It picks the first process. A first workflow in production has a guide price of $12,000 and takes three to five weeks. The exact price is fixed after a call or after the review. The three packages are on the AI Agent Development page.
How is this different from building AI into our own software product?
Product AI needs deeper work around release control, quality and ownership. That is covered on the Production AI for Product Teams page.
Bring a process, we will scope the first workflow
You do not need a finished AI plan. Bring a process, a department, or a problem, and we map the first workflow worth building. We check the data, tools and access it needs, define what stays under human control, set what success looks like and prepare a build plan.
Building AI inside a software product? Product AI needs deeper work around release control, quality, and ownership.