Vision & data systems
Annotation, dataset versions, retrieval and model workflows, with image-relative geometry and inspectable artifact lineage.
DataHubEnterprise / Technical partnerships
Build the system
behind the idea.
Production AI and computer vision need data workflows, useful interfaces and a way to operate. AlgoFly connects those parts through hands-on engineering.
Discuss a technical partnershipA working foundation
Start from mechanisms.
Build for your workflow.
These are examples already implemented in AlgoFly projects. A partnership starts by deciding which of them belong in your system.
Where we can work together
Operational computer vision
Geospatial analysis, shelf recognition and camera-event review that connect model output to an operator’s next action.
Private application case studiesInfrastructure & networking
Native Rust connectivity, direct peer transport, relay fallback and remote terminals, files and application proxies.
PortHubConnected devices & input
Room presence and sensor history, plus voice, keyboard and touchpad workflows for supported desktop or embedded receivers.
HomeSense Voice KeyboardAn engagement with clear edges
Agree on the work.
Make progress reviewable.
A focused discovery engagement, a scoped implementation, or continued product development can fit different starting points. The sequence below is a planning framework; deliverables and timing belong in the agreed scope.
- 01
Architecture & discovery
Map the workflow, existing systems and acceptance criteria.
A written scope, constraints, integration boundaries and a proposed first delivery.
- 02
A scoped build
Implement a useful slice with review points and representative data.
Working software, integration checks and an acceptance review against the agreed scope.
- 03
Deployment & handover
Prepare the chosen environment and make the operating path understandable.
A release plan, configuration guidance and agreed documentation or training.
- 04
Continued development
Extend the system as requirements and evidence change.
Prioritized follow-on work and support arrangements agreed for the project.
Indicative engagement budgets Monthly planning ranges
A starting point for a conversation with Nitin. These are indicative monthly engineering budgets, with scope, capacity and delivery terms agreed in a proposal.
| Engagement scope | Per month | Typical planning duration |
|---|---|---|
| Small, focused scope | €3,000 | 1–3 months |
| Medium engagement | €6,000 | 6–9 months |
| Larger programme | €12,000 | 12–24 months |
EUR is the reference currency. Project duration, infrastructure costs, taxes, payment currency and support are agreed separately in the proposal. This is planning guidance, not a binding quotation.
Engineering decisions, made explicitly
Your operating environment
belongs in the design.
Existing implementation is useful evidence. Deployment requirements, ownership and service commitments are decisions we make with you.
Data & ownership
Implemented example
DataHub separates source images, annotations, version outputs and exported artifacts.
Read the implementationAgree for your project
Data ownership, retention, deletion, permitted model use and licensing.
Access & transport
Implemented example
PortHub implements scoped access and pinned DTLS peer connections; DataHub authorizes project and worker operations.
Read the implementationAgree for your project
Identity provider, roles, network boundaries, encryption requirements and secret management.
Deployment & compute
Implemented example
DataHub has registered worker execution; traffic analytics separates camera processing from the review application.
Read the implementationAgree for your project
On-premises or private-cloud topology, customer GPU compatibility, capacity and release process.
Operation & recovery
Implemented example
Traffic analytics exposes camera and worker health. DataHub uses recoverable publication and checksummed artifacts.
Read the implementationAgree for your project
Monitoring destinations, backup and restore verification, incident responsibilities and support terms.
Start with the engineering question
What needs to work better?
Bring the current workflow, the integration you need, or the constraint you are trying to resolve.