Futurelab is an AI agency that helps businesses put AI agents to work: finding the workflows where agents pay off, building them around existing systems and running them with human review. Services cover voice agents, agent development, workflow automation, custom AI tools and forward AI deployment.
AI agents for business
Futurelab is an AI agency that finds where agents pay off in your business, builds them around your systems and runs them with your people, from the first workflow to the tenth.
Futurelab Studios: OpenAI Select Partner · Claude Partner Network
Trusted by teams at PepsiCo · ITC · SBI · Syngenta
The best first agent takes a task your team repeats every day, has the information it needs and can be checked. Pick a team to see where we usually start.
Reads the CRM, recent emails and the news before every meeting, writes a one-page brief and drafts the follow-up for the rep to approve.
Answers routine questions on chat, email or phone from your policies and order data, and hands complex cases to a person with a summary.
Collects updates, chases missing inputs, routes work to the right owner and reports exceptions, across a defined process.
Extracts fields from invoices, claims and contracts, checks them against rules and queues anything unusual for review.
Answers employee questions from HR policy, walks new joiners through onboarding and escalates anything personal or sensitive.
Monitors competitors and the category, summarises what changed and drafts on-brand content for a marketer to review.
Agents for business are not one product. Depending on where you are, we help you choose, build, connect or run them. Each service has its own page.
Voice agents for call centres and customer lines, with a human always one sentence away.
Chatbots for customers, staff and field teams, grounded in your sources and able to act.
Ask your documents anything and get an answer with its source, respecting who may see what.
AI agents on WhatsApp for distributors, retailers, field teams and frontline staff.
Sales assistants and an AI layer on your CRM, for inside sales and field teams.
Invoices, claims and contracts read, checked against your rules and posted to the ERP.
Screening with reasons, scheduling, onboarding and an HR helpdesk on your policies.
Shelf checks, demand forecasts and assistants for store staff and field teams.
Ask your business data questions in plain language and see the working behind every answer.
How we design and build governed agents with a clear job, trusted context and review.
Agents and automations connected across the tools your team already uses.
Purpose-built AI products for a specific team, shipped and published as case studies.
Our engineers embed inside your team to build and run agents in production.
A ranked portfolio of agent opportunities and a roadmap, before you build.
These are products Futurelab built and runs, each an agent or assistant with one job. Status is shown as it stands today.
A field sales agent: CRM access, route suggestions and call summaries logged automatically.
A knowledge agent: accurate answers from your own documents, for staff or customers.
A client agent: tracks every relationship, flags risks and suggests the next step.
A meeting agent: joins, transcribes and delivers clear action items.
A drafting agent: client-ready proposals with sources, exported to Word, PDF or PowerPoint.
A research agent: market and competitor research gathered and summarised, now in beta.
An agent is worth having when it gives time back to people, moves work faster and stays inside the rules your business already has.
Repetitive research, drafting, data entry and follow-ups move to agents, and your team spends the day on judgment and relationships.
Agents work around the clock and pick up a task the moment it arrives, so customers and colleagues are not left waiting.
Scoped permissions, review points and a record of every action, so leaders know what each agent did and why.
Agents with a job, not a demo Every agent we build has a named owner, a measure of success and a person who reviews its work. If it cannot be checked, it does not go live.
Start where you are. Some clients come with a workflow already chosen; others want help deciding where agents belong at all.
Find and rank the workflows where agents would pay off first.
One agent, one workflow, built and tested on your own data.
Several agents across teams, on shared foundations.
We monitor, maintain and improve the agents after launch.
Four steps, each with something you can see, so you always know what you are paying for and what comes next.
Map where your teams lose time to repetitive work, and pick the workflow with the clearest payoff and owner.
You get: A ranked list of agent opportunities
Design its job, knowledge, tools and guardrails, and build a working version on your data.
You get: A working agent your team can try
Run it alongside the team, measure quality and time saved, and fix what does not hold up.
You get: Results you can take to leadership
Launch with monitoring and owners, then add the next agent on the same foundations.
You get: Live agents with reporting and support
Embedded deployment with the full advisory team—custom AI tools that shortened planning cycles and improved coordination.
Technology leadership and product delivery—from AI Sachiv at state scale to meeting intelligence and learning platforms adopted as a digital public good.
13+ years in marketing and growth leadership at Google, Paytm, Airtel and Amul.
13+ years across business strategy and technology transformation at Amul, Wipro, PepsiCo and Mondelez.
An AI agent is software that can carry out a task, not just answer a question: it reads the information it needs, takes actions in your systems and hands its work to a person to check. A business agent has one clear job, an owner, scoped access and a measure of success.
With one workflow your team repeats every day, where the information the agent needs already exists and its output can be checked. Account briefings, customer support, document processing and policy questions are common first agents.
We find the workflows where agents pay off, design and build the agents around your systems, test them with the people who do the work and run them after launch. We can also train your teams to work well alongside them.
A focused pilot on one workflow usually produces a working agent your team can try within a few weeks. Going live depends on integrations, data access and the review your risk and security teams need.
The agents we build take repetitive work off people and hand their output to a person to approve. The aim is to give your team time back for judgment, relationships and the work only they can do.
Yes, as part of a wider agent programme rather than on their own. Our MeetEasy product joins meetings, transcribes them and delivers action items, and we built AI meeting capture for Piramal Foundation. For legal teams, our document AI reviews contracts against your playbook and keeps a searchable contract register.
Each agent has scoped permissions, approved knowledge sources, clear limits on what it may do, human review points and a log of every action. We agree these with your security and risk teams before launch and monitor quality afterwards.
Tell us about your business and the work that slows your teams down. We will suggest where an agent could help first, and what it would take.