Impact archive

Proof, not promises.

Deployment records for AI systems that capture, qualify, route, and recover commercial demand.

Additional work captured
~£10K
Reported by Ekron in the first 3 months
Operating-cost reduction
83%
Voice-agent deployment
Inboxes connected
16
One routing workflow

Selected deployments

Surveying · Ekron Surveyors

How Ekron Surveyors cut call-handling costs by 83% with an AI receptionist.

The client reported around £10K in additional work/leads captured in the first three months; this is not presented as booked revenue.

83%operating-cost reduction
£20K/yrcall-centre cost saved
Read the case study

Construction materials · MIX-STROY

How MIX-STROY qualifies 100+ leads a day across five inbound channels.

The live workflow handles more than 100 inbound leads per day, giving sales reps structured, ready-to-quote opportunities instead of raw chat threads.

100+leads per day
5inbound channels
Read the case study

Construction materials · Stroyassortiment

How an AI inbox router connected 16 manufacturing inboxes in two weeks.

The deployment connected 16 inboxes, processed 1,123 emails at an average routing time of 1.2 seconds, and replaced manual department-by-department triage with structured routing.

16inboxes unified
1,123emails processed
Read the case study

Real estate · Dubai · Real-estate broker agency

A WhatsApp agent qualifies property enquiries and books viewings into Google Calendar.

A working WhatsApp workflow that turns a property enquiry into a confirmed Google Calendar viewing slot.

WhatsAppproperty qualification
Google Calendarviewing booked
Read the case study

Commercial operations · Hobopro

How HoboPro built corporate email infrastructure, then automated the inbox.

A repeatable implementation that starts with reliable email infrastructure, then adds AI-based routing and classification instead of bolting automation onto an unstructured inbox.

2 layersinfrastructure and automation
AIclassification and routing
Read the case study

Healthtech · Mediann.dev

Technical advisory for a multi-agent nutrition-assistant product.

The product team moved from the need for a nutritionist chat to a tailored multi-agent system design shaped around their requirements.

AI/MLspecialist advisory
Multi-agentsystem design
Read the case study

AI software · Confidential startup

A multi-agent AI receptionist built to work across CRM and booking systems.

A configurable foundation for an AI receptionist across amoCRM, Bitrix24, YClients, Google Calendar, and Yandex Calendar, plus settings interfaces and a simplified codebase.

5CRM and booking integrations
~6Klines removed
Read the case study

How to read these cases

What these AI automation case studies cover

These deployments cover AI receptionists, lead qualification, email routing, CRM handoff, booking, and private operational AI. Each case explains the initial bottleneck, the system built, and the available deployment evidence—not just a feature list.

Where a client supplied a commercial outcome, it is clearly labelled as client-reported. Where only technical or operational evidence is available, the case states that limitation rather than inventing a return-on-investment figure.

Start with the case that matches the channel where work is currently being lost: calls, inboxes, messaging conversations, or disconnected CRM records. Then use the linked solution page to understand the broader system behind it.