Real problems first
We start from the workflow, the users, and the operating constraint. The model choice comes after the business problem is clear.
Applied AI · Product engineering
Intelligent products, built for the real world.
Web apps, copilots, and ML systems where AI is part of the workflow — not a demo on top.
Live system
v 2026.5
Product surface
Portals · dashboards · tools
Intelligence
Copilots · vision · ML
What we do
A small applied-AI shop. The breadth and shape of the work, in four numbers.
4
AI modalities
Language · Vision · Audio · Tabular & time-series
3
Deployment modes
Cloud, hybrid, or on-prem when security demands it
Design → Product
One team, end to end
From idea, through MVP, to monitoring in production
1
Small team, no handoffs
The founders who scope the work also ship the code
Philosophy
The product matters as much as the model.
Model, interface, workflow, and infrastructure have to fit together. We design them as one system.
We don't bolt AI onto a generic product. We redesign the product around the exact place intelligence creates leverage.
Fast iteration, honest scope
We prototype quickly, test against real data, and keep only the AI that creates measurable leverage for the product.
Custom intelligence
We combine models, software, and domain knowledge around your business instead of forcing your team into a generic AI wrapper.
Small team, direct ownership
The people who define the architecture are the same people who implement, ship, and monitor it in production.
Expertise
Product and AI capability, designed together.
A web app reimagined for the AI era, a copilot, a vision pipeline, an audio workflow, or a predictive system — wired into the software your team already uses.
Track 01
AI-empowered web applications
Customer products, operator workbenches, and internal portals where AI becomes part of the daily workflow instead of a disconnected add-on.
assistantssearchautomationdecision support
Track 02
Custom chatbots and copilots
LLM and VLM assistants grounded on your documents, tickets, catalogs, procedures, and customer context.
RAGtool usemultimodal chatworkflow actions
Track 03
Vision and document intelligence
Image-to-text, video-to-text, OCR, inspection flows, classification, extraction, and multimodal retrieval for operational teams.
documentscamera feedsinspection imagesvideo archives
Track 04
Audio and language pipelines
Speech transcription, call analytics, diarization, summarization, sentiment, and structured outputs from conversations and recordings.
callsmeetingsvoice notessupport interactions
Track 05
Predictive ML and analytics
Forecasting, anomaly detection, scoring, recommendation, optimization, and classical machine learning where predictive signal matters most.
demandriskqualitybehavior
Track 06
Production ML infrastructure
Data pipelines, experiment tracking, evaluation, deployment, observability, and iteration loops that keep intelligent systems reliable over time.
ML OpsmonitoringCI/CDserving
AI era redesign
The right model, data, and interface — for the domain you actually work in.
We match the model family to the domain object: contracts, tickets, calls, images, video, reports — whatever the workflow needs.
Domain objects we work around
contractsinvoicessupport ticketsknowledge basesproduct catalogscamera feedscalls and transcriptswarehouse imagesquality reportscompliance records
SaaS or customer portal
Add grounded assistants, document understanding, recommendations, and workflow automation directly inside the product.
Operations platform
Unify text, images, video, and audio into one decision surface for teams handling real-world processes at speed.
Field or mobile application
Turn camera capture, voice notes, and sensor inputs into structured reports, QA checks, and follow-up actions.
Lifecycle
From design and experiments to production and iteration.
The model is one piece. The system around it — data, orchestration, evaluation, deployment, monitoring — is the work.
01
Frame the problem
Clarify user workflow, available data, accuracy requirements, latency, and business success metrics.
02
Experiment fast
Prototype with the right model family and quickly test the workflow against real examples and edge cases.
03
Ship the MVP
Build the smallest product that proves the operational value, not just model quality in isolation.
04
Integrate and harden
Connect the system to business logic, data flows, auth, logging, and human review loops where needed.
05
Monitor and improve
Track usage, quality, drift, and product signals so the system keeps improving after launch.
Demos
Past work, ongoing products, and reference builds.
A look at the kind of AI-enabled products and pipelines we ship.
Reference slot
Document intelligence workspace
Search, extract, summarize, and route contracts, forms, invoices, and knowledge-heavy business documents.
Good fit for finance, compliance, legal operations, and back-office teams.
OCR / VLMRAGhuman reviewworkflow automation
Reference slot
Vision quality and inspection pipeline
Turn product images or live camera feeds into classification, anomaly checks, traceability, and reporting.
Useful for manufacturing, warehousing, field inspections, and logistics operations.
computer visiondetectionevent streamingdashboards
Reference slot
Audio operations copilot
Transform calls, meetings, and voice notes into transcripts, summaries, action items, and searchable memory.
Helpful for support, sales, field teams, and customer success workflows.
speech-to-textNLPretrievalanalytics
The team
Direct ownership, from discovery to deployment.
No handoff chains. The team that frames the product also builds and ships it.
Gerasimos MarkantonatosFounding partner / Engineering
Architecture, delivery, and production reliability stay in the same hands.
Ioannis SkagkosFounding partner / Product and AI systems
The product matters as much as the model. We design both together.
Contact
Tell us what you want to build.
Email us directly, or request the structured intake form. The best briefs cover users, workflow, data, integration, and the metric that matters.
Direct line
hello@smarkventures.com
Start with a short description of the product, users, data, and the operational problem you want solved.
Structured brief
Request the Google Form intake
Prefer a structured questionnaire? Ask for the Google Form and we will send the intake format we use for new product discussions.