Custom AI Solutions
Custom AI solutions powered by a cross-border research network—LLM fine-tuning, RAG, and from-scratch models for NLP, recommendation, and time series.
Overview
Cybernetic Labs delivers end‑to‑end custom AI solutions, from LLM fine‑tuning and RAG systems to from‑scratch model development across NLP, recommendation, and time series forecasting. A cross‑border virtual lab structure blends academic rigor with real‑world engineering to ship production‑ready systems quickly. Our expertise complements our flagship products, Synkvault for enterprise AI and Zekoder for legacy system modernization, and tailored solutions for industries like Fintech and Real Estate.
Capabilities
Our expertise spans the full spectrum of modern AI development.
LLM Fine-tuning & Alignment
Instruction tuning, DPO/RLHF, domain adaptation, safety and red‑teaming, evaluation harnesses, and model distillation.
NLP & Information Intelligence
Classification, NER, summarization, translation, semantic search, retrieval pipelines, and multilingual support.
Recommendation Engines
Candidate generation, ranking, re‑ranking with behavioral and content signals, cold‑start strategies, and online A/B experimentation.
Time Series Forecasting
Univariate and multivariate models, hierarchical reconciliation, seasonality and promotions modeling, anomaly detection.
System Integration
RAG architectures, data pipelines, feature stores, batch and real‑time inferencing, and secure deployment on cloud or on‑prem.
Methodology
Our delivery model is designed to move fast without sacrificing rigor.
Research Network
A cross-border virtual lab blending academic rigor with real-world engineering.
10+
PhD Holders
20+
Masters-Level Experts
Supported by a larger cohort of Masters students.
Quality and Safety
Evaluation
Task‑appropriate metrics and benchmarks, offline and online testing, fairness checks, and regression guards.
Security & Privacy
Data governance, PII handling, encryption in transit and at rest, and role-based access.
Reliability
CI/CD for models, canary or shadow deployments, monitoring for drift and degradation, and automated retraining hooks.
Tech Stack
Flexible deployment to meet latency, cost, and compliance goals.
Engagement Models
Milestone-Based Programs
- Multi-workstream initiatives
- Research sprints
- Staged deployments
Deliverables
LLM Artifacts
Model weights or adapters, evaluation reports, safety cards, prompts/tooling playbooks, and integration interfaces.
NLP Systems
Endpoints and pipelines for classification, extraction, summarization, or multilingual tasks with monitoring dashboards.
Recommendation Engines
Candidate generation and ranking services, feature pipelines, experiment frameworks, and business KPI tracking.
Time Series Solutions
Forecasting models with backtesting reports, scenario tooling, alerting policies, and data connectors.
Documentation & Transfer
Architecture diagrams, runbooks, test suites, deployment manifests, and training sessions for internal teams.
Frequently Asked Questions
What industries are supported?
Solutions span finance, healthcare, e‑commerce, logistics, media, and public sector, with domain‑specific adaptation as needed.
Is on-prem deployment available?
Deployments can be cloud, hybrid, or fully on‑prem with strict data residency and access controls.
How is success measured?
Clear KPIs set at discovery time, covering model accuracy or business metrics such as conversion uplift, inventory turns, or forecast error reductions.
Who owns the IP?
Unless otherwise agreed, client ownership is supported for bespoke models, code, and data derivatives created under the engagement.
How fast is a typical PoC?
Most PoCs complete within 4–8 weeks, depending on data readiness and scope.
Join the Network
Clever, ambitious researchers are welcome to join a growing network of consultants.
Contact Us
For discovery, proposals, or capability briefings, contact Cybernetic Labs' core team to scope goals, timelines, and success criteria.
Get in Touch