Software & Applied AI Engineering
Complex systems.
Built end to end.
I build the tools operators use to find the right policy, review a request and recover a failed delivery.
I take it from the first operator workflow
through release and handover.
Explore the work ↓Selected work
Products, platforms & independent builds01Workflow engineering
Flowdesk.
One enquiry.
One CRM record.
Replay a webhook, interrupt delivery, then retry it. The operator can see the failure and recover the approved enquiry without creating a second record.
Self-initiated demo · fictional data · CRM simulator
Search that traces a passage back to its source.
I work on ingestion, retrieval and AI-provider integration. In an offline check, updating a sample returns policy from 14 to 30 days changed the retrieved passage. A question about opened parcels still retrieved a rule for unopened parcels. That is a case I would test before putting a support assistant in front of customers.
Role & project status +
Data pipelines / retrieval / RAG / provider integration
Platform project · public demo unavailable
03Mathematics · AI interface
Lemma
∫ A mathematical notebook built around handwriting.
Handwritten input and AI features in a single product. My role covers requirements, prioritisation, user scenarios and development coordination.
Role & project status +
Product requirements / user journeys / delivery coordination
Product project · overview
04Android · cloud storage
Folio
↗ File transfer and backup to S3-compatible storage.
An Android application for moving and backing up files. My role covers requirements, priorities, user scenarios and development coordination.
Role & project status +
Android product / S3-compatible storage / user workflows
Product project · overview
Engineering scope
The whole product.
The details that matter.
Product thinking and operational experience, backed by hands-on engineering.
01Product → release
Turn an ambiguous business problem into requirements, architecture and a working product. Own the decisions across backend, interface, integrations and deployment.
02ML, NLP & applied AI
Build retrieval into the product and test it on questions people actually ask. Trace each cited passage to its source and check when the assistant should abstain.
03Visibility & control
Structured logs, traces and relevant metrics. Make failures diagnosable, recovery deliberate and quality, latency and cost measurable where they matter.
Working stackJava · Python · Go · JavaScript · Vue
The engineer
Dmitry Popov
Software & Applied AI Engineer
with product and operational experience.
My background connects enterprise software, insurance workflows, product development and operational work with clients and contractors. I work across the business process and the system that supports it.
Enterprise experience +
Medical assistance software for operators and insured users: organising care, arranging appointments and connecting people with services. Organisation names and internal details remain confidential.
I use AI agents to accelerate development. Technical decisions, quality checks and commitments to the client remain my responsibility.
A focused way to start
One clear scope.
A working result.
Send a webhook that creates two records, a question your search gets wrong or a task your team still does by hand.
- 01 / DEFINE
Reproduce the problem.
We use one example to agree the expected result, the cases to test, the fee and the delivery date.
- 02 / DELIVER
Build it and run it again.
I implement the change, rerun the example and show where your team can see stalled work or unsupported answers.
- 03 / HAND OVER
Hand it to the operator.
You get the code, test results and a short guide to running the feature and handling the failures we covered.
Quoted after a written brief. If the system needs investigation first, we agree a separate discovery stage. Additional workflows and ongoing support are scoped separately.
See the three ways to work together ↗