Service — AI & automation
AI that is wired into the work, not beside it.
An AI feature is only as useful as its access to your data, your systems, and the decisions that already have owners. We build the connective layer that turns a capable model into something your team can actually rely on.
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Agentic workflows
Chatbots get forgotten. Autonomous agents wired into real databases and business tools run companies.
Goal-driven multi-agent orchestration, tool use, and automated process pipelines with human-in-the-loop governance.
- Multi-step agent workflows equipped with deterministic tool calling
- Human-in-the-loop review for high-risk decisions and approvals
- Complete audit logging and reversible actions for every automated step
Task Directive
“Reconcile fleet inventory drift between ERP and dispatch databases, trigger restock order if inventory < 50.”
ReAct Reasoning Agent
Plans 3 distinct sub-steps: fetch current delta, calculate required stock, queue ERP update with state rollback checkpoint.
Dynamic Function Calling
Circuit Breaker Gate
Write operation detected ($8,400 purchase order). Supervisor pauses execution pending security rule confirmation.
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Enterprise RAG
An AI system without verifiable retrieval is hallucinating with confidence.
Enterprise retrieval pipelines grounded in your proprietary knowledge base, with precise source attribution.
- Semantic chunking, dense vector embeddings, and hybrid keyword search
- Cross-encoder re-ranking so the most relevant passages reliably win
- Strict citation provenance and deterministic refusal when facts are absent
Semantic Search
Matches concepts & semantic intent across un-tokenized corpus via embedding distance.
Exact Term Matching
Guarantees exact article numbers, SKU codes, policy clauses, and acronyms are never missed.
Unified Candidate Pool
Deduplicates and merges top 100 results into a single context stream passed to Cross-Encoder.
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Model fine-tuning
Prompt engineering hits a hard ceiling. Fine-tuning bakes deep, permanent domain intelligence into the model.
Adapting open-weight foundation models and custom weights directly to your domain, eliminating prompt limits.
- Domain adaptation and parameter-efficient tuning (LoRA/QLoRA) on proprietary data
- Model distillation producing specialized models that run 10x faster and cheaper
- Custom evaluation pipelines measuring task accuracy against production ground truth
Teacher vs. Distilled Specialized Student Model
Distillation transfers the reasoning capability of a 70B parameter teacher model into a compact 8B student model fine-tuned on your exact production dataset.
70B Parameter Teacher
8B Specialized Student
AI Integration Architecture
AI works best when it is connected to the work around it.
Syscov designs AI capabilities as an integral part of your product architecture and operational pipeline — not as a disconnected novelty or an isolated wrapper.
Engineering Principles
Three things we hold to.
How we approach every engagement — the non-negotiables that keep systems maintainable, compliant, and buildable.
Start from the process
We map the work before choosing a model. A tool picked before the target process rarely survives contact with it.
Guardrails before launch
Schema, PII boundaries, and citation requirements are part of the build, not a later review.
Measurable, or not shipped
If we cannot tell whether it is working, it does not go to production.
Engagement Outcomes
Production deliverables you own from day one.
Every engagement produces tangible codebases, automated pipelines, and operational specs your internal team actually runs.
Production Inference Engine
Fault-tolerant LLM and agentic workflow orchestration with streaming token state machines, retries, and fallback cascades.
- Multi-model failover & provider routing
- Streaming backpressure & connection state
- Sub-200ms TTFT latency optimization
Automated Benchmark Suite
Continuous testing harness measuring hallucination rates, semantic precision, and prompt drift against real production data.
- Golden benchmark dataset evaluation
- Synthetic adversarial edge-case suites
- CI deployment blocking on accuracy dip
Guardrails & PII Sanitizer
Strict JSON Schema validation, prompt injection shields, and automated PII anonymization before payloads touch model endpoints.
- Zero-PII compliance validation pipeline
- Deterministic schema output enforcement
- OWASP LLM Top 10 automated defenses
Model Ops & Telemetry
Cost-per-token analytics, vector store re-indexing automation, distributed tracing, and team maintenance training.
- Real-time token & egress unit economics
- Vector index sync & maintenance scripts
- Internal team pairing & prompt playbooks
Tell us what you are trying to build.
Bring the constraint that worries you most. That is usually the fastest way to work out whether this is the right service for the job.