AI Solutions
We build AI systems that sit inside your product, not next to it. That means LLM workflows with real guardrails, retrieval pipelines you can audit, and predictions wired into the decisions they're meant to influence.
LLM applications
Agentic workflows, RAG systems, and copilots using OpenAI, Anthropic, or self-hosted open models.
Retrieval & embeddings
Pipelines across Postgres / pgvector, Pinecone, Weaviate — chunking strategies tuned to your corpus.
Predictive analytics
Forecasting, churn, scoring, and anomaly detection using XGBoost, LightGBM, or deep models where they earn their keep.
NLP & document AI
Extraction, classification, summarisation — we've shipped proposal-writing and contract-triage systems into production.
Evaluation & guardrails
Offline eval harnesses, prompt regression tests, PII redaction, and policy layers before anything ships to users.
MLOps
Model registry, A/B rollout, drift monitoring — built on SageMaker, Vertex, or vanilla Kubernetes.
- Weeks one and two: data audit, feasibility scan, and a working baseline model.
- Weeks three through eight: iterative model and product integration sprints.
- Shadow-mode release first, then a guarded rollout — never straight to users.
- An evaluation dashboard your team actually reads each week.
- Shipped models with serving, monitoring, and rollback
- An evaluation suite and prompt / model registry
- Reproducible data pipelines running in your cloud
- Team enablement: one workshop and a written playbook
Who this actually fits.
- Companies whose competitors just shipped a copilot
- Ops teams sitting on years of unstructured documents
- Products where a confident prediction changes user behaviour
Scope a ai solutions engagement.
Send a paragraph about what you’re trying to ship. We’ll come back with a call time, a named team lead, and a rough cost band — usually inside 24 hours.