AI engineering for operations-heavy companies
Work that takes your team a week should take an afternoon.
We design, build and run custom AI systems that take manual work off your staff. Start with a paid assessment: in two to four weeks you get a costed roadmap of what to automate first, and what it is worth.
Fixed scope. Fixed fee. You own everything it produces.
01 — The problem
Your best people spend their week moving information around.
Someone copies numbers from one system into another. A customer waits two days for an answer that exists in an inbox. A report gets rebuilt by hand every Monday because nothing joins the data together.
None of this shows up as a line item. It shows up as headcount you cannot redeploy, deals that go cold, and errors you pay to correct. Software can now do most of it reliably, if someone builds it for the way your operation actually runs.
02 — What we build
Four kinds of system. Each one already running for a client.
Agents that answer customers and act on it
Voice and chat that take the call, ask the right questions, and complete the booking or the ticket. Volume goes up, headcount does not.
Tango
Live voice call to a booked itinerary in 4 minutes.
Internal agents that end manual data work
Reconciling, tagging, checking, re-keying between systems. The work still gets done, and nobody does it by hand.
OrionQ
80% fewer manual tasks on revenue data.
Checking work before it goes out
Claims, applications, quotes and contracts reviewed against your own rules for what is missing or wrong, before a customer or a regulator sees it.
Wranx
Errors reaching a customer down 94%.
Everything that arrives, turned into a record
Applications, invoices, forms, contracts, supplier emails. Read, understood, and filed into your systems correctly, without a person opening each one.
Arcafeed
1,200 supplier emails a week, filed without a person opening one.
03 — Selected work
Named clients. Measured outcomes.
04 — The cost of doing it manually
What one manual process costs you
people on my team spend hours a week each on a manual process. An hour of their time costs about $.
Every month you do it manually
$15,912 lost
Every year with 24x7 AI agents
$190,944 saved
The routine share is your estimate. On a 30-minute call an engineer tells you the real one, and what building it costs.
Start saving →05 — How we work
Five stages. You know what you get, and when.
Assessment
We sit with the teams doing the work, map the processes, and price the opportunities. You receive a process map, a prioritised list, a costed roadmap and the risks named plainly.
Weeks 1–4 · Fixed fee
Decision
You take the roadmap to your board with the numbers already done. If you stop here, you keep everything we produced and owe nothing further.
End of week 4
First system live
We build the highest-value item on the roadmap and put it in production with the before-and-after measured. One process, working, in front of your staff.
Weeks 5–10
Build out
Either a fixed-scope project against a defined brief, or an embedded team working your roadmap in your timezone. Two-week increments, a working demo at the end of each.
From week 10
Operate
Systems like these need someone watching them. We monitor, correct and improve, and report monthly on what the system handled and what it saved.
Ongoing · Monthly
06 — Your three options
The five questions your board will ask.
Us, a Big Four firm, or building the team yourself — answered in as few words as we can manage.
Agentic Labs
A small senior team, in your hours
Big Four firm
Process, scale, a defensible name
Hire in-house
Permanent capability you own
07 — Clients
In their words.
“Ritik is incredibly smart and very astute. Works to understand the problem to be solved and his solutions have been on time and on budget. His communication is steady and he is very collaborative. We will continue to work with him on current and future projects.”
Stefan MercierCo-Founder, Landmark Educational Tours
“I would highly recommend Agentic Labs! They completed the work needed to speed up our site quickly and efficiently. They were knowledgable and made recommendations that will help us in the future.”
Persia ShahkaramiMarketing Head, Wranx
“Agentic Labs delivered good work on this development project and I enjoyed working with them. Their communication was top-notch, they met all deadlines, and their skills were strong. I enjoyed working with them and will likely have additional jobs for them in the future.”
Raunaq MokhaCTO, Arcafeed
“Ritik stands out as an outstanding developer, demonstrating not only intelligence and proactivity, but also a penchant for innovation, a strong sense of involvement, and unwavering commitment.”
Aymen MontasserFounder, SAM
“Ritik's skills, knowledge, and work ethic exceeded all my expectations. From the very beginning of the project, Ritik demonstrated a deep understanding of the task at hand. He not only delivered what was asked but also provided invaluable insights and recommendations to optimize the bot's performance.”
Alec KleinmanFounder, Aspyre Digital
“Agentic Labs was great in assisting us with the initial process of our website documentation and the roadmap to follow in arquitecture and front/backend development. We will be working together many more times i hope.”
Enrique BarbaCEO, Apolo P2P
Nine named references in full, with titles and companies, plus three more on request. Ask for them in the call.
Ritik Kansal
Co-founder
- Before
- Software development engineer at Amazon; 5G network security at Oracle before that.
- Depth in
- Agent orchestration, RAG and retrieval, the AWS infrastructure agents run on.
Farazul Haque
Co-founder
- Before
- Product manager at Mastercard Data & Services; electronics engineering at IIT Kharagpur.
- Depth in
- Agent product design, agentic search, automating work people do not want to check.
09 — Questions we get asked
The things a board will ask you.
If something here is not answered clearly enough to repeat internally, ask us in the call and we will put it in writing.
Where does our data live, and who can see it?+
In your infrastructure and your accounts wherever possible. Where a third-party model is used, we use enterprise terms with no training on your data, and we list every service, what it touches and where it is hosted in the assessment. Access is limited to the named engineers on your contract.
Who owns what you build?+
You do. Code, prompts, documentation and the roadmap are yours on payment, in your repositories from day one. Nothing is held back to keep you on a retainer.
What if the assessment says this is not worth doing?+
Then it says so, and you have a documented answer for the board for a fraction of the cost of finding out the hard way. It has happened. We would rather tell you in week three than bill you for a year.
How is the engagement governed?+
A named lead on our side, a named sponsor on yours, two-week increments with a working demo at the end of each, and a written status you can forward without editing. Scope changes are priced before they start.
Who actually does the work?+
Senior engineers from our own team, named in the contract, in Bengaluru and working your hours. No subcontracting, no unnamed bench, no swap-out after signature.
What do we need to provide?+
A sponsor who can make decisions, a few hours with the people who do the work today, read access to the relevant systems, and someone from IT for the security review. Roughly a day a week during the assessment.
How long before something is actually working?+
A costed roadmap in two to four weeks. One system live in production, with the before-and-after measured, by around week ten.
10 — Next step
Book the AI Opportunity Assessment.
Two to four weeks, fixed fee, fixed scope. You get a process map, a prioritised list of what to automate, a costed roadmap and the risks named. It is a decision you can make without a board paper.
- —A 30-minute call first, with an engineer, not a salesperson.
- —NDA before anything sensitive is discussed.
- —You keep everything the assessment produces.
Pick a time
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