AI built into your existing systems
For work that outgrew the team doing it. Built into the ERP, CRM and support platforms you already run — and your own infrastructure when the data cannot leave.
02What we do
Agents, infrastructure, and leadershipMost engagements begin with one and grow into another.
AI Agents
Agents that complete a workflow start to finish — quoting, configuration, support and reporting, working against your live data.
Delivered for SSN, IrisPro and dlivrd.io.
AI Enablement
The infrastructure agents depend on — data pipelines into your source systems, private and on-premise model deployment, and governance over who can access what.
Delivered for SSN and Hemab.
AI Advisory
Where AI fits in your operation and where it does not, program delivery in regulated environments such as pharma and finance, and fractional CTO or COO leadership.
Delivered for Merck.
03Outcomes
What changedEach figure comes from a time study in the client’s own systems.
04Selected work
Three bottlenecksEach started as a proof of concept.
SSN · On-premise
Quoting was too slow to be worth doing on small deals
SSN sells data-center servers, storage and networking, and none of their data was permitted to leave their building. We built the engine that works out which parts fit together, checks live ERP inventory and prices the result. At five minutes a quote instead of two hours, those deals are now worth fulfilling — SSN runs over 800 a month. A second service tracks competitor listings and adjusts pricing, previously a daily manual task.
IrisPro · Financial services
The monthly close took weeks of analyst time
IrisPro sells an FP&A platform to hedge funds, banks and other financial firms — analysts who have to trace every number back to its source. We built the reporting agent behind it. It cites every answer, produces the recurring reports, works through batches of files and builds the finished decks.
dlivrd.io · Logistics
Driver issues arrived faster than the call center could answer them
dlivrd’s 10,000 drivers report order and fulfillment issues by text and in-app chat, more than 2,000 a day. The agent now answers first: it retrieves the order, classifies the issue and its priority, resolves what it can, and escalates the rest to a person with the full history attached.
05How we work
From audit to productionWe measure before we build.
Audit
We audit how the work runs today — the systems, the handoffs, and where the time goes. You get it in writing.
Design
We pick the workflow worth doing first, weighed on value against effort and payback, then specify exactly what we will build and what it costs.
Prove
We build against your real systems in a test environment, then show you and validate it before anything expands.
Implement
It goes live across the remaining cases, with your people trained, the system documented and monitoring in place.
Optimize
We stay on to tune accuracy, coverage and running cost, then take the next workflow.
06Meet the team
Where we learned thisWaterfield, Merck, Roche, AWS, Twilio.
Dmitriy Fridkin
Founder
Previously Director of Engineering for AWS, Twilio and AI at Waterfield Technologies, engineering manager at Merck, and technical product lead at Roche.
Johnie
Integration Lead
Previously engineering manager at Waterfield Technologies, with ten years as lead developer and architect on AWS, Twilio and Salesforce integrations.
Ali
Process Consultant
Six Sigma certified. Previously senior process consultant for the Veterans Administration and Enterprise Systems Partners, building the frameworks that define data governance and compliance.
07Let's talk
Start with an auditDescribe the process. We will tell you if it is worth automating.
The audit is scoped and paid. The fee comes off the build if you proceed.