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AI & Intelligent Automation
Intelligence that does real work.
THE PROBLEM
The demo worked. Production is a different question.
Many AI initiatives stall between a promising prototype and a system people can trust. Answers drift, costs are unclear, and nobody can explain why the model did what it did.
WHAT NEURALSHARKS DOES
We design AI around a defined task, representative data, and an evaluation you can rerun. Retrieval, model integration, guardrails, and human review are part of the architecture from day one, not patches added after launch.
CAPABILITIES
- Use-case discovery and feasibility
- Retrieval-augmented generation (RAG)
- Bounded agents and tool use
- LLM integration, fine-tuning, and model training
- Autonomous bots with guardrails and monitoring
- Workflow and document automation
- Evaluation suites and regression checks
- Human-in-the-loop review and escalation
TYPICAL OUTCOMES
- Answers grounded in your own sources, with references
- Automation that routes exceptions to the right person
- Quality, latency, and cost you can measure release over release
TECHNOLOGIES
GO DEEPER
- AI developmentTurn a promising model into a dependable product.
- AI agentsPurpose-built agents with clear boundaries and human control.
- AI automationBring intelligence to repetitive work and complex workflows.
- LLM integration & model trainingPut language models to work inside your products, tuned to your data.
- Autonomous botsBots that keep working around the clock, inside clear limits.