Questions and answers.
Technical parameters, deployment timelines, and engineering methodologies for prospective enterprise partners.
What AI services does ObsessLabs architect?
We engineer comprehensive AI infrastructure including custom LLM fine-tuning, autonomous multi-agent swarms, RAG architectures, computer vision pipelines, low-latency voice models, and scalable MLOps compute clusters.
What is the typical deployment timeline for enterprise projects?
Proof-of-architecture prototypes typically ship in 2 to 3 weeks. Production-grade systems with high-availability infrastructure and continuous telemetry deploy over 6 to 10 weeks.
Do you integrate with existing enterprise stacks or build greenfield?
We support both. We seamlessly interface with existing private cloud VPCs, legacy databases, and API gateways, or architect standalone sovereign intelligence stacks.
How do you distinguish between pre-trained APIs and custom models?
Pre-trained models provide rapid prototyping for generalized tasks. Custom fine-tuned models (using LoRA, PEFT, or full weights) yield strict domain precision, lower latency, and zero vendor lock-in.
How do you guarantee model deterministic reliability and prevent regressions?
We construct continuous adversarial benchmark suites, synthetic edge-case verification, and live embedding drift telemetry to ensure zero hallucination in critical decision pathways.
What compliance and data governance protocols are enforced?
All systems are deployable in air-gapped environments or private VPCs with strict zero-retention policies, HIPAA compliance verification, and SOC2-aligned boundaries.
Have specific requirements?
Our engineering team is available for architectural consultations.