MLOps & Infrastructure
Production pipelines, model versioning, and observability tailored to your stack. We automate retraining, validation, and deployments with safety checks and rollback strategies to minimize risk.
🚀 Services
Kotik AI provides focused services that span the full lifecycle of machine learning and generative systems. We build proofs of concept to demonstrate impact quickly, then help harden successful prototypes into reliable production components. Our engagements always begin with measurable success criteria: what signal will indicate value, and what monitoring will keep it safe. We place emphasis on interpretability, fallback strategies, and operational playbooks so teams can maintain trust while models evolve. Our blend of engineering, research, and product design helps organizations move from uncertainty to repeatable, governed AI delivery.
Production pipelines, model versioning, and observability tailored to your stack. We automate retraining, validation, and deployments with safety checks and rollback strategies to minimize risk.
From feature engineering to model architecture selection, we deliver reproducible experiments and clear evaluation metrics. Our research deliverables include baselines, ablations, and human evaluation where appropriate.
Bias assessments, privacy reviews, and intervention design. We produce mitigation plans, governance documentation, and monitoring strategies to detect drift and harmful patterns early.
Design systems, generative art pipelines, and content workflows with human review loops. We emphasize guardrails and provenance so generated content is auditable and brand-safe.
Task-oriented assistants, retrieval-augmented tools, and moderation flows. We focus on context retention, safe fallbacks, and monitoring user satisfaction signals in production.
Interfaces, feedback mechanisms, and human-in-the-loop design that make model outputs actionable and understandable. We build flows that enable teams to tune behavior safely over time.
Kotik AI follows an engagement model designed to reduce uncertainty and produce durable results. We begin with a discovery phase to surface constraints, available data, and success metrics. During discovery we run small experiments and rapid prototypes that are designed to be decisive: either they demonstrate value quickly or they reveal necessary pivots. When a prototype shows signal, we transition to a production phase that includes engineering for reliability, observability, and cost control. We implement monitoring that tracks data drift, performance regressions, and user-facing metrics. Our delivery also includes documentation, runbooks, and handoff sessions so your team can operate and maintain models with confidence. Governance is built into the workflow: model approvals, scheduled audits, and clear rollback plans make it straightforward to manage updates safely. We prioritize transparency, reproducibility, and measurable business outcomes so AI becomes a manageable, trustable part of your product strategy.
Schedule a short discovery to align on goals, data access, and timelines. We provide a clear statement of work and milestones so teams can plan confidently.
We offer fixed-scope prototypes, time-and-materials engagements for research and iteration, and retainer arrangements for long-term partnerships. Each engagement includes clear acceptance criteria and reporting cadence.