AI agents for the work between your systems.
We find the multi-step work your team still does by hand, put a price on it, and build AI agents to take it over.
What this work has done for clients
Under 5s
To answer every inquiry on WhatsApp, email and web
Treasures Int Contracting, Dubai
22 hrs
Of manual data entry removed every week
Toros Distribution
An agent finishes what a chatbot only describes.
Agentic AI plans the steps, uses your tools and checks the result before it moves on.
Traditional RPA
- Follows fixed rules
- Breaks when a screen changes
- Cannot make a judgement call
- Needs constant upkeep
Fine for stable, rule-only tasks
Generative AI
- Answers one prompt at a time
- Forgets between sessions
- Cannot take actions
- A person still acts on the output
Good for drafts, stops at text
Agentic AI
- Plans a task across several steps
- Acts in your CRM, email and databases
- Keeps memory and context
- Works around the clock, with human review where it matters
Finishes the job, with people on the risky calls
Five things every agent we ship has.
Plenty of products sold as AI agents are decision trees with extra steps.
It plans before it acts
An agent breaks a goal into steps and changes course when something shifts halfway through.
Every tool call needs permission
API calls, database writes and sent messages all pass a permission layer with logs, approval limits and a dry-run mode.
It remembers long jobs
Work survives a crash and can be replayed step by step when something needs debugging.
A person takes the unsure calls
When the agent is not confident, the action goes to someone on your team with the full context. You set that line.
Every run is tested and watched
Test cases score whole runs step by step. Dashboards track cost per run, success rate, escalations and drift.
Start where people are the glue.
Look for the person who spends the day moving information between tools. That work is usually the first thing an agent should take.
Answer and qualify inbound leads
Agents pick up leads from any channel, check them against your ideal customer and route each one to the right person.
Research every prospect before the call
An agent pulls recent news, LinkedIn activity, tech stack and job postings into a short brief in your CRM.
Triage support requests
Routine requests get handled. The rest reach your team with account details attached. Works with Zendesk, Intercom and custom help desks.
Read contracts and invoices
Agents pull the main terms out of PDFs, scans and emails, flag risks and route approvals.
Watch competitors daily
Pricing, launches, job postings and news, tracked every day and sent to leadership as a short weekly digest.
Chase project updates
Agents chase subcontractors, flag blockers and send status reports, so your managers stop doing it by hand.
Three layers, each picked for the job.
n8n
Workflow orchestration
Connects your tools, handles triggers and routes work between agents. It can be self-hosted when data privacy calls for it.
LangGraph
Agent state and logic
Keeps track of state, so an agent can plan, branch, retry and hold context through a long task.
GPT, Claude and Llama
Model layer
GPT for complex reasoning, Claude for documents and long context, Llama for high-volume or self-hosted work. We swap models as better ones arrive.
How one run moves
Trigger: webhook, schedule or event n8n routes the work LangGraph agent Model reasons Action in CRM, email or API Logged, or sent to a person
Priced before anything is built.
Weeks 1-2
Audit
We find the repeatable multi-step work your people do and price each fix. You get a ranked plan.
Weeks 1-2
Architecture
We decide which agent does what, which tools it can touch and where a person signs off.
Weeks 3-10
Build and connect
Agents wired into your CRM, email, databases and APIs, with error handling, logging and fallbacks from day one.
Weeks 11-14
Test and launch
Agents run in a sandbox, then alongside your team, before they take over. Documentation and training come with it.
Questions about agentic AI.
What is agentic AI?
Agentic AI is AI that works toward a goal on its own. It plans the steps, uses tools, makes decisions and adjusts to what happens, without a person approving each step. A chatbot answers one prompt. An agent carries out a sequence of actions across real systems until the job is done.
What is the difference between agentic AI and generative AI?
Generative AI answers a prompt with text. It does not take actions, remember across sessions or follow a task through several steps. Agentic AI adds planning, action and memory, so one agent can research a prospect, update your CRM, send an email and log the result as a single workflow.
What business use cases are best for agentic AI?
Jobs that take several steps, need a person to coordinate them today and follow clear decision rules. Common examples are lead qualification, sales research, support triage, document processing, competitor monitoring and project coordination. If someone on your team spends the day moving information between systems, start there.
How long does it take to deploy an agentic AI system?
Most agent systems take 8 to 14 weeks from audit to production. Two or three agent workflows on existing integrations can go live in 6 to 8 weeks. Multi-agent systems with custom model work usually take 12 to 16 weeks.
How much does it cost to build AI agents in India, the UAE, the USA and the UK?
A focused agent project usually costs ₹8-15 lakh in India, AED 40,000-75,000 in the UAE, $15,000-30,000 in the USA and £12,000-25,000 in the UK. Multi-agent systems that span several departments are larger programmes. The audit gives you a fixed price before we build anything.
Can AI agents make mistakes, and how do you keep them safe?
Yes, agents get things wrong, so we design for it. Every action passes a permission layer, uncertain decisions go to a person, every run is logged, and tests catch problems before changes go live. You decide which actions an agent may take on its own.
Which work should an agent take off your plate?
Tell us which workflow eats your team's week. The audit prices it and tells you whether an agent should do it at all.
Most businesses we meet have paid for an AI tool nobody uses. We start from your numbers, so the first build is chosen by payback.
Zain Khan and Anwar Sheikh
Founders, OutGrow
Outgrow
Intelligence
Studios.