Discovery and technical validation
Define the user, workflow, data, baseline, risks, and success measures before committing to a large implementation.
✓AI development services
AI development services from strategy to production.
Build the whole product around the AI capability. We connect models, data, workflows, interfaces, integrations, infrastructure, and release ownership so the system can survive real usage.
End to endmodel, product, and cloud
Web + mobilecustomer and operator interfaces
Productiondeployment and support
What we deliver
Built around the use case, not the buzzword.
Sketric provides custom AI development services for agents, generative AI, computer vision, product interfaces, integrations, cloud, and MLOps.
AI and application engineering
Build model services, retrieval, business logic, APIs, databases, and the web or mobile experience as one system.
✓Integrations and workflow design
Connect CRMs, knowledge sources, messaging, storage, payments, internal systems, and approval steps.
✓Cloud, MLOps, and release
Deploy with observability, access controls, cost visibility, evaluation, rollback planning, and a clear operating handoff.
✓Where this creates leverage
A strong fit when the difficult part is the whole system.
We scope delivery around the operating reality, the people responsible for it, and the evidence needed to make the next decision.
A custom AI capability is central to the product
Off-the-shelf software cannot express the domain logic, workflow, data boundaries, or user experience the product needs.
An internal team needs a specialist delivery partner
We can own the AI workstream, a defined subsystem, or the full product while keeping architecture and decisions visible.
The system must work beyond a controlled demo
We design around representative data, failure modes, latency, cost, security, human review, and maintainability.
Evidence in production
Proof from products and client systems.
Owned applications and selected client work show how AI decisions behave after launch.
Computer vision + product
PlateSniper
A completed plate-detection and OCR proof of concept across edge, mobile, backend, and operator-review components.
↗ Computer vision + analyticsMulti-camera traffic analytics
An eight-input workflow combining video analysis, aggregation windows, spreadsheet outputs, and dashboard review.
↗Questions teams ask
Useful answers before the first call.
Direct answers for teams deciding whether an AI system is worth building.
What is included in custom AI development services?+
The scope can include discovery, data and model work, RAG, agents, computer vision, APIs, web or mobile interfaces, integrations, cloud deployment, evaluation, monitoring, and support.
Can you modernize an existing AI prototype?+
Yes. We can assess the prototype, identify production gaps, preserve useful work, and build the missing product, reliability, security, integration, and operating layers.
Do you work with OpenAI, Anthropic, Google, AWS, and open-source models?+
We design around the provider and deployment approach that fit the use case, data requirements, latency, cost, and existing stack. A solution can combine commercial APIs, cloud services, and self-hosted models.
How long does an AI development project take?+
It depends on data readiness, workflow complexity, integrations, evaluation requirements, and release scope. We define milestones around the riskiest assumptions first instead of promising a generic timeline before discovery.
Who owns the software and project artifacts?+
Ownership and licensing are defined in the engagement agreement. Client work is kept distinct from Sketric-owned products, and the delivery scope makes those boundaries explicit.
Have a project in mind?
Bring us the workflow, constraint, or ambitious idea.
We will help identify the narrowest useful starting point and the evidence needed to move forward.
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