AI agentsSaaSIn production
Build · Agentic AI
AI agents and automation
AI agents that do real work for any team, from support and operations to finance, engineering and sales. Built with your people, taken from pilot to daily use, and measured on what they save.
Who it is for: Teams that lose hours every week to repetitive work with clear rules, and leaders tired of pilots that never ship.
- Typical length
- Six to twelve weeks to a first agent in daily use
- Start with
- AI and Growth Diagnostic
The problem
Gartner expects more than 40% of agentic AI projects to be cancelled by the end of 2027, because of rising costs, unclear value and weak risk controls (TechCentral, 2025).
Most fail for the same reasons. The job was never pinned down, the agent cannot reach the right data, nobody measured a starting point, and nobody decided what a person must approve. Some never needed an agent at all.
What you get
- Support: sorting tickets and drafting replies, with a person approving what goes out
- Operations: checking documents, claims and orders against your rules, and flagging what needs a person
- Finance: matching invoices, chasing payments and preparing reports
- Engineering and IT: sorting incidents and answering questions from your own documentation
- Sales and marketing: researching and qualifying leads, following up and keeping the CRM current
- Any team: answers from your own documents and data, with access rights kept in place
With every agent
- Tests that measure quality before and after launch
- Monitoring, and a record of every decision
- Documentation, runbooks and training for the people who will run it
How it works
Each stage has a check it must pass before the next one starts.
Define
The job, the starting point it must beat and what a person must approve. Check: an agreed measure of success. If the job does not need an agent, we say so here.
Build
Connected to your systems and tested on real cases. Check: it passes the tests on your own data.
Pilot
A small group uses it on live work, with approvals on. Check: it beats the starting point.
Daily use
Rolled out, monitored and handed over. Check: your team runs it without us.
Is it right for you?
Right for you if
- A team spends hours each week on repetitive work with clear rules
- You ran an AI pilot that never made it into daily work
- You need AI that can show what it did and why, to an auditor or a client
Not the right fit if
- The job needs no AI: simple automation will do, and we will tell you
- You want a demo, not a system people use every day
Related work
Proof
The product is a set of AI agents that find fraud, waste and abuse in health insurance claims. Our team designed the platform, led the build and took it from pilot to paying clients. Its first review found $3.2M a year in waste that the insurer's existing tool had rated fully compliant.
Led by our team before Burraq Quantum was formed.
How we work
- Built for daily use from the first week: designed with your engineers, with security checked as we build.
- Permission first: an agent acts only with current, checked permission, and a person approves where the stakes are high.
- Rules the system enforces: your rules apply on every step, instead of sitting in a prompt as advice.
- A record of everything: every decision is logged, so the agent can be fixed, audited and improved.
- The model that fits the job: from Anthropic, OpenAI or others, not one vendor's platform.
These methods come from the AI governance work our team developed, three of which are patent pending.
By sector and city
Mumbai
- FintechAI agents for fintech teams in Mumbai that handle support, document checks and lead follow-up, with people approving what matters and the savings measured.
Questions
Asked about this service
What is an AI agent?
Software that plans and carries out tasks with several steps, using your tools and data, instead of answering one question at a time. It can sort support tickets, check documents, match invoices or keep a CRM current, with a person approving the steps that matter.
How long does it take to build an AI agent?
Six to twelve weeks for a first agent in daily use. The range depends mostly on how many of your systems it has to connect to.
What happens when the agent gets something wrong?
The design expects it. A person approves the high-stakes steps, tests catch errors before launch, monitoring flags a drop in quality, and every decision is logged, so the cause can be found and fixed.
Will it work with our current systems?
Yes. Agents connect to the tools you already run, such as your CRM, helpdesk, ERP and document stores, instead of sitting beside them as one more system.
Where does our data go?
Usually it stays in your own environment. Which models are used, and where they run, is agreed in scope, so the setup meets the data laws that apply to you, such as Saudi Arabia's PDPL or India's DPDP Act.
What happens when the AI model changes?
We re-run the tests before any model change goes live. Because the agent is not built around one vendor, a model can be swapped when a better or cheaper one appears.
Who runs it after handover, and who owns it?
Your team runs it, with documentation, tests and training from us. Ownership and support after handover are agreed in scope before the build starts.
How is an agent different from automation tools such as Zapier?
Automation follows fixed steps. An agent can read, decide and choose its next step within the rules you set. We use plain automation wherever it is enough.
Start here
Start witha straightanswer.
A 30-minute call to see whether we can really move your numbers. You leave with a clear next step, even if we never work together.
