RAG & Search
Retrieval & grounding
Chunking, embeddings and re-ranking tuned per corpus, so the model answers from your documents with the passage attached.
Refuses rather than guesses3 in the index
Technology • Engineering • AI • Cloud
From Ideas to Production-Ready Technology.
Syscov helps turn ambitious digital ideas into thoughtful, scalable technology built for real-world production.
What we build
Technology shaped around the problem, not a preset package.
Web & product platforms
Web experiences built on a real backend, not a template with a form bolted on. We handle the interface, the data behind it, and the parts that have to keep working once traffic and content actually grow.
Learn moreFull-stack engineering
Every layer treated as one system, because most failures happen in the gaps between them. Front-end, services, data and deployment are designed together, so nobody ends up owning half a problem.
Learn moreAI & automation
Intelligence wired into the work people already do rather than parked beside it. Retrieval over your own sources, evaluation you can actually trust, and a human kept on the decisions that carry risk.
Learn moreCloud & infrastructure
Production environments built to be operated, not just launched. Deployment, monitoring and recovery are designed in from the start, so the person on call at 2am is not guessing at what broke.
Learn moreBuild AI with Syscov
We build AI that survives real users, real data, and real load.
Retrieval, agents, evaluation and serving — the parts of an LLM system that decide whether it still works on day four hundred, not just on day one.
Multi-Agent Systems
Agent systems
Tool calls, held state and a supervisor that can halt a run mid-flight — an agent with write access needs a stop button.
Supervised, with rollback1 in the index
Real-Time Inference
Production inference
Model routing, batching and provider failover held inside a p99 latency budget — the slowest one percent of requests, which is the part users actually notice.
Fails over on degrade3 in the index
What we bring
From a brief on a whiteboard to a system that holds under load.
Complex builds rarely fail on a single skill. They fail in the handoffs — between design and engineering, between the model and the product, between shipping it and running it. Syscov keeps those disciplines in one team so there is no gap to fall through.
- 12
- Systems documentedin the case-study index
- 6
- Engineering disciplinesheld in one team
- 12
- Daysfrom audit kickoff to decision
Technologies
The languages, frameworks & platforms we build in.
Python
AI LanguageTraining, inference services & the data pipelines feeding both
PyTorch
AI FrameworksFine-tuning and custom model work where an API is not enough
Model APIs
AI & ModelsResilient integration across OpenAI, Claude & Gemini
Retrieval pipelines
AI & RAGChunking, reranking & grounded citations from your data
Vector stores
AI DatabaseHigh-dimensional similarity indexing for semantic search
Agent workflows
AI AgentsBounded tools, state machines & human-in-the-loop gates
Inference serving
AI RuntimeGPU-backed serving, batching & streaming responses under load
Evaluation harnesses
AI QualityBenchmark suites that catch regressions before a release ships
Working together
Four ways teams bring us in.
Most projects start in one of these shapes. If yours does not, say so — the shape matters less than whether the problem is one we can actually help with.
End-to-end build
You have the problem and the mandate, but not the team. We take it from architecture through to production and hand over something your engineers can run without us.
Syscov holds the whole line
Best when there is no in-house team yet
Embedded engineering
Your team is already building and is missing a discipline — AI, infrastructure, security, or front-end depth. We work inside your process and leave a codebase your engineers recognise.
Slotted into your team
Best when you have a team but a gap
Rescue and takeover
A build has stalled, or the people who wrote it are gone. We take ownership of what already exists and get it stable before anyone argues about replacing it.
Handover from a stalled build
Best when a project is already in trouble
Audit and roadmap
Before committing budget, get a technical read on what the work actually takes — what is buildable in your stack, what it costs, and what to do first.
We read it, you decide
Best before a decision is made
Syscov Your team Owners gone
Not sure which one fits? Describe the problem and we will tell you which shape it is — including if it is not one for us.
Careers
Engineers who want the hard half of the problem.
Syscov works on systems where the interesting part is the constraint, not the framework. If that is the kind of work you want, we would rather see what you have built than a list of keywords.
No open roles right now
We still read open applications. Send what you have worked on and what part of it you owned — that tells us more than a CV does.
Send an open application