AI agents, working inside real systems.

The problem

Production and quality data lived in SAP, but pulling a simple answer meant raising a request to the MIS team and waiting a day. Line managers made calls on stale numbers.

What we built

• A query agent that reads SAP production and quality modules and answers plain-language questions
• Shift-wise summary reports pushed automatically each morning
• A leadership AI awareness session, then hands-on workshops for engineering and operations

The result

Line managers get answers in seconds instead of raising tickets, and the MIS team stopped spending its week building the same recurring reports.

The problem

VAHAN dashboard reporting was rebuilt by hand every cycle, and every marketing campaign needed a developer to hand-code the HTML email before it could go out.

What we built

• An automated pipeline that pulls VAHAN data and generates the dashboard report on schedule
• An HTML email generator feeding straight into Adobe Campaign
• Validation checks so nothing goes out with broken data or layout

The result

Reports arrive without anyone building them, and the marketing team ships campaigns without waiting in the developer queue.

The problem

Floor staff would not adopt a new app. Complaints, checklists, and compliance records were on paper or lost in phone calls, so nothing was traceable.

What we built

• A WhatsApp agent handling complaints and escalations with automatic ticket creation
• Hindi voice-note support, so workers speak instead of typing
• Daily checklists and compliance logging with a supervisor dashboard

The result

Operations run on the app workers already use. Every complaint now has a ticket, an owner, and a timestamp, with no new software to learn.

The problem

Leadership knew AI mattered but had no view of where it would actually pay off inside a heavy manufacturing process.

What we built

• A structured discovery questionnaire circulated across departments before the visit
• An on-site factory walkthrough mapping each process step to automation potential
• A prioritised roadmap ranking opportunities by effort against payoff

The result

A concrete, sequenced plan instead of a generic AI strategy, with the first build targets agreed by the end of the session.

The problem

Students and faculty knew the AI headlines but had never built anything agentic themselves.

What we built

• A hands-on masterclass covering Claude Projects, agentic tools, MCP servers, and Skills
• A live build where every participant shipped a lead-qualification agent in the room
• A follow-on personal branding workshop

The result

Participants left with a working agent they built themselves, not notes about one.

The problem

Humanities and social science students were being told AI would reshape their fields, with no practical entry point.

What we built

• A no-code curriculum built around research, writing, and analysis workflows
• Live sessions building tools without touching a terminal
• Prompt and workflow templates students could keep using afterwards

The result

Non-technical students left using AI in their actual coursework rather than treating it as a separate subject.

The problem

Chapter members ran substantial businesses but were using AI, if at all, as a novelty rather than an operating tool.

What we built

• A practical session on where AI moves the business and the P&L
• A dedicated hands-on track for the spouses group
• Phone-first workflows members could apply the same day

The result

Members walked out with AI in their daily routine rather than on their someday list, and several converted into MCode engagements.

The problem

A spoken-English platform with heavy tutor operations and support load, and no shared AI capability across the team.

What we built

• A five-weekend structured AI series across functions
• Support and tutor-ops workflows drafted with AI in the loop
• CRM-connected follow-up drafting for the sales and success teams

The result

AI moved from a few curious individuals to a shared way of working across the company.

The problem

Publishing across every social platform meant reformatting the same idea by hand, over and over, for each channel.

What we built

• An agent chain that takes one source idea and produces channel-native versions
• Direct scheduling and publishing through the Blotato API
• Performance pulled back in so the next run learns from the last

The result

A single input becomes a scheduled multi-platform run, with no manual reformatting step in between.

The problem

Powerful agentic build tools land with users who have never structured an agent workflow and stall at the blank page.

What we built

• Applied build sessions taking a real brief to a working app
• Reusable patterns for scoping, prompting, and connecting tools
• Content and walkthroughs for a non-technical audience

The result

Users get past the blank page and ship something real in their first session.

The problem

Coordination staff spent their day on scheduling, documentation, and routing enquiries rather than on patients.

What we built

• Enquiry triage and routing with escalation rules for anything clinical
• Documentation and summary drafting with a human sign-off step
• Scheduling and follow-up coordination connected to existing systems

The result

Admin time drops while every clinical decision stays with a person, by design.