AI Development Services

We build comprehensive custom AI applications, including custom Large Language Model (LLM) implementations, machine learning forecasting engines, NLP text extractors, computer vision anomaly detection networks, and autonomous task-solving agents.

Typically, a sandboxed Proof of Concept (PoC) takes 4 to 8 weeks. Training, fine-tuning, and integrating a production-ready model into your database pipelines takes 3 to 6 months depending on structural complexity.

Not necessarily. Our team provides full data engineering capabilities. We can ingest, audit, clean, and structure raw unstructured data (like PDFs, audio recordings, or logs) to set up training datasets.

Data security is our primary focus. We configure private cloud network boundaries, isolate models inside local sandbox infrastructures, encrypt data in transit and at rest, and strictly comply with ISO 27001, SOC 2, and HIPAA guide rails.

Yes. We specialize in building secure microservice APIs and middleware connectors to link new AI pipelines seamlessly with your existing CRMs, ERPs, workflow orchestration systems (like Camunda), and cloud applications.

We are technologically agnostic. We use state-of-the-art closed source models (OpenAI GPT, Claude, Gemini) via secure enterprise endpoints, as well as open source architectures (Llama, Mistral) which can be hosted completely locally on your private servers.

Yes. Post-launch model performance monitoring is critical. We establish automated drift alerts, track latency footprints, check logic drift, and implement secure model retraining loops to keep your models highly accurate.

Costs are structured entirely by project scale, integration points, and model specifications. After our discovery call, we outline a transparent milestone-based cost proposal so your organization sees clear Strategic value at every phase.