Autonomous LLM agents and AI workflows for your business. Custom pipelines, retrieval over your own data, and agents that complete work rather than just answer questions.
Six core agentic ai solutions capabilities engineered to turn strategy into measurable results.
Task-specific chains with prompt versioning, evaluation sets, and regression tests before anything ships.
Multi-step agents with tool access, memory, budget limits, and a defined hand-off to a human.
Vector search over your documents with chunking strategy, re-ranking, and row-level permissions preserved.
Classification, extraction, summarisation, and intent detection tuned on your domain language.
Training, serving, monitoring, and retraining loops with drift detection and rollback.
Every action logged and replayable, with policy checks, cost ceilings, and evaluation dashboards.
OpenAI, Anthropic, LangChain, LlamaIndex
Every agent we build is aimed at a specific piece of work, triaging a queue, drafting a document set, reconciling records, answering from your own corpus. Each is evaluated against a held-out set before it ships and comes with guardrails, cost ceilings, and a defined hand-off to a human.
Retrieval runs over your data with row-level permissions intact, and every action an agent takes is logged and replayable, so you can audit exactly what was done and why.
Trusted across industries to solve real business problems at scale.
Extraction, classification, and routing across contracts, claims, and invoices with human review on low confidence.
Retrieval-grounded answers over your knowledge base, resolving 60%+ of routine queries with citations.
Semantic search across wikis, tickets, and repositories with each user's existing permissions preserved.
Multi-step agents that operate real tools (ticketing, CRM, internal APIs) under budget and policy limits.
Hover a use case, each one feeds the same shared context.
Measured across 12 tools in the delivered stack.
Battle-tested tools and platforms powering every agentic ai solutions engagement.
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