Applied AI, deployed

We build and deploy AI systems that cut manual work from critical business processes.

We turn a high-value process into a production system connected to your existing tools. Your team stays in control, and the result is measured against a business metric.

See how we deploy

Focused scopes for SMEs, mid-market teams, and enterprise business units.

Choose one valuable process

Connect the systems and data

Keep people in control

Measure the business result

What we actually do

From a messy process to a dependable system.

The AI model is one component. The real work is understanding how the job is done, connecting the right information, handling exceptions, and proving that the result helps the business.

Find the constraint

We observe the work, map the handoffs, and choose a scope where automation can release meaningful capacity or improve a critical decision.

Build in the business

We connect the system to the tools and data already in use. No new destination for employees to remember and no generic chatbot layer.

Design for control

We define what the system may do, when a person must decide, and how every action is reviewed, logged, and recovered.

Prove and improve

We compare performance to the starting point, fix what breaks, and expand only when the evidence supports it.

Example deployments

Start with a clear business use case.

A use case simply means one recurring job where AI can save time or improve a decision. It could be replying to property leads, screening applicants, following up with buyers, or tracking competitors.

6 to 9 weeks to production

WhatsApp CRM for real estate

Operational friction: Property enquiries arrive at all hours, and the buyer's budget, location, and timeline stay buried in WhatsApp chats. Agents respond unevenly and warm leads are easily forgotten.
System we deploy: A WhatsApp assistant connected to the CRM that answers the first enquiry, asks a few useful questions, records the lead, routes it to the right agent, and reminds the team when follow-up is due.

Outcome to measurerespond to every new enquiry within five minutes and reduce qualified leads lost without follow-up by 30 to 50%.

6 to 10 weeks to production

Recruiting screening and coordination

Operational friction: Recruiters read the same information across CVs, application forms, and notes, then lose time arranging interviews and updating candidates. Strong applicants wait while the administration catches up.
System we deploy: A recruiting assistant that organises each application against the role criteria, prepares a short evidence-based brief for the recruiter, and coordinates the next step once a person approves it.

Outcome to measurereduce recruiting administration time per vacancy by 40 to 60% while keeping every screening decision human-approved.

6 to 9 weeks to production

Sales follow-up and pipeline

Operational friction: Salespeople finish calls with useful context in their notes and inbox, but CRM updates and follow-up messages happen late or not at all. Managers then forecast from an incomplete pipeline.
System we deploy: A sales assistant that turns meeting notes and emails into a concise CRM update, drafts the follow-up, and flags deals that have no owner, next step, or recent activity.

Outcome to measuregive sellers 20 to 35% more time with customers and reduce qualified opportunities without a next step.

6 to 10 weeks to production

Marketing and competitive intelligence

Operational friction: Teams manually check competitor sites, announcements, campaigns, and customer signals, then spend more time assembling slides than deciding what the changes mean.
System we deploy: A research assistant that monitors agreed public sources and internal performance data, groups meaningful changes, links each finding to its source, and prepares a concise weekly brief.

Outcome to measurereduce weekly research and reporting time by 50 to 70% and surface material competitor changes within one business day.

Explore all use cases

A clear first engagement

Bring us one recurring job that should work better.

We begin with a focused deployment review. Together we determine whether the use case is valuable, feasible, and safe enough to build. We define success before code is written.

See the full approach

DEPLOYMENT REVIEW