01
Specialized AI or ML work is outside the current team
The partner can own the client relationship and product direction. seKer AI can take the model, RAG, or integration work that would otherwise stall the project.
For software houses and agencies
Your AI and engineering partner,behind the scenes.
Extend your technical capacity with specialized AI, machine learning, and software development support. We help software houses and digital agencies deliver complex work without expanding their in-house specialist teams. When a brief needs RAG, an LLM feature, or a forecasting model, we build the agreed technical slice inside your stack and hand it back for you to deliver.
White-label, co-branded, or named subcontractor delivery. NDA available before you share details. Direct projects are welcome too.
seKer delivery pipeline
Example engagement flow · not live data
- 01
Brief
Partner scope
- 02
Build
seKer engineering
- 03
Deliver
Partner ships
Pipeline focus
RetrievalLLM appsAPIsHandoff
- Scope and deliverable agreed
- Integration path defined
- Partner review points
Example steps
- Corpus indexedvector store ready
- Eval passretrieval quality check
- API contracthandoff to partner stack
You keep the client relationship. seKer AI takes the agreed technical slice and hands it back for delivery.
Why partners come to us
The gaps we fill
These are the practical problems software houses and agencies run into when a brief needs AI or extra engineering depth.
02
Delivery demand is ahead of hiring
When a pipeline is already full, adding a specialist hire is slow. Project-based engineering support covers a defined scope without a permanent role.
03
An existing product needs an AI feature
Many briefs are not greenfield. We work inside the current architecture, APIs, and release process so the partner can keep shipping the rest of the product.
04
A single engagement needs extra technical depth
Some projects only need help on one slice: retrieval quality, evaluation, a FastAPI service, or a forecasting model. That can be scoped on its own.
05
The partner wants capacity, not another brand in the room
White-label or behind-the-scenes delivery is an option we can discuss. The partner stays the face of the work; we agree communication and responsibilities up front.
How collaboration works
A simple path from brief to delivery
The partner stays close to the client. seKer AI takes the agreed technical slice.
Share the requirement
A partner sends the project scope, technical constraint, or client brief. We review what is already decided, what is missing, and whether the work is a fit.
We build the agreed slice
seKer AI provides the relevant engineering work — models, RAG, APIs, or product features — against a defined deliverable, stack, and communication rhythm.
Deliver together
The partner presents and ships the work to its client. Responsibilities, review points, and how we appear (or do not appear) are agreed before build starts.
Capabilities
Focused technical work
A shorter list, on purpose. These are the areas we can support with substance — not a catalog of every possible AI service.
RAG and knowledge assistants
Retrieval systems that answer from a defined knowledge base, with source tracking and a path to iterate on quality.
Useful when Consultants, support teams, or internal staff spend too long searching documents that already exist.
AI integrations and LLM applications
Add language-model features to an existing product: copilots, document tools, content workflows, and API-backed assistants.
Useful when A partner has a client who wants AI inside a current product, but the in-house team should not pause other delivery to learn the stack.
AI agents and workflow automation
Tool-using agents and automations that complete multi-step work, with human review on the steps that need it.
Useful when Repetitive operations, research, or hand-offs are eating delivery time that should stay with the partner’s client work.
Custom software, APIs, and backend integrations
Application, API, and integration work so AI features sit cleanly inside the product instead of as a disconnected demo.
Useful when The AI piece is only useful if it talks to the existing CRM, database, auth, or client portal — and that engineering still has to ship.
Machine learning and predictive analytics
Forecasting, scoring, and classification models connected to the data and workflows a team already uses.
Useful when A project needs predictions or ranking, not only a chatbot, and the current team lacks ML delivery capacity.
Live demos
Try the work, don't take our word for it
Four interactive demos that run in your browser on sample data. They are not client projects. Each shows how we build a piece of the work.
RAG
Document Q&A with sources
Ask a question, get the answer with the passage it came from, or a refusal.
Open demoMachine learning
Forecasting with an honest backtest
A forecast with a prediction band, tested against simple baselines it has to beat.
Open demoLLM integration pattern
Ticket triage with human approval
Structured output, a confidence gate and an audit log around an AI step.
Open demoPartner tool
Client brief scope checker
Paste a client brief and see which parts are AI work and what to clarify first.
Open demoWhy seKer AI
A technical partner, not another agency pitch
Differentiators we can stand behind without inflating the story.
Specialized AI and engineering capacity
Partners can add LLM, RAG, ML, and backend work without standing up a permanent specialist team first.
Project-based collaboration
Engagements are scoped around a deliverable. We can support a full build or a defined part of a larger project.
Work that fits existing products
Most useful AI work has to live inside current codebases, data stores, and release habits. That integration work is part of the job.
Clear technical ownership
We agree what seKer AI builds, what the partner owns, and how reviews happen — before the work starts.
A practical build mindset
The aim is a usable system the partner can hand over or keep extending, not a slide-deck prototype that cannot leave a notebook.
FAQ
Straight answers
If a policy is still agreed per project, we say so.
Notes
From the seKer AI blog
Published writing on Medium — useful context, not a substitute for a project conversation.
Have a project that needs additional AI or engineering expertise?
Share a short brief. We’ll tell you whether the work is a fit and how a collaboration could be scoped.