AI-driven engineering for the enterprise
Captivolt helps enterprises build secure AI agents, RAG systems, automation workflows, data intelligence platforms, and AI-native software that work with real data, real systems, and real governance. We combine strategy, engineering, evaluation, security, and capability transfer so AI moves from ambition to production.
Built for CTOs, CIOs, CISOs, Heads of AI, VP Engineering leaders, and enterprise decision-makers who need AI to survive production.
Buyer pathways
Products & Accelerators
We do not start every engagement from a blank page. Captivolt brings reusable architectures, validation systems, governance models, and delivery accelerators that help enterprises build faster without losing control.
Technical depth
Enterprise AI requires more than a model. Captivolt designs the full operating architecture: data, knowledge, tools, agents, applications, evaluation, governance, security, and observability.
ERP, CRM, ITSM, HRMS, document stores, databases, APIs — the systems of record AI must respect.
Ingestion, indexing, semantic modelling, metadata, permissions, lineage — engineered so AI answers from governed truth.
LLMs, tools, agent orchestration, workflow rules, human approvals — controlled autonomy, by design.
Copilots, dashboards, automations, portals, internal applications — where AI meets real work.
Evals, prompt regression, retrieval quality, hallucination checks, task success — VeriCore patterns wired into delivery.
AI inventory, risk classification, access control, audit evidence, incident response — AegisIQ in operation.
Monitoring, drift detection, cost tracking, latency, feedback, and continuous improvement.
Interactive diagnostic
Answer a few questions to identify whether your organisation should start with AI strategy, AI build, AI assurance, or AI capability development. Eight questions, no sign-up.
Solutions
Real Work
We show proof carefully: real anonymised engagements where confidentiality requires it, reference architectures where the work is proprietary, and artefact-led examples that demonstrate how we think and build.
Captivolt helped define the operating model, role architecture, capability framework, hiring validation, and ramp approach required to build repeatable AI/ML capability.
Captivolt developed an enterprise AI framework covering use-case intake, governance, risk classification, accountability, evidence, and leadership oversight.
Captivolt guided leadership on AI transformation priorities, use-case sequencing, operating model, value pools, and delivery readiness.
Why Captivolt
Strategy is tied directly to build, evaluation, governance, and capability transfer.
Agents are designed around enterprise systems, access controls, workflow rules, human oversight, and observability.
We test LLM, RAG, and agentic systems before and after release.
AI risk, security, evidence, and accountability are built into the architecture.
Your teams leave stronger, with runbooks, standards, operating rhythms, and practical skills.
AI platforms provide powerful capabilities. Captivolt helps enterprises apply those capabilities inside real operating environments — designing the architecture, integrations, evaluation, governance, security, workflows, and capability transfer required for production use.
Method
Assess AI readiness, data, systems, workflows, governance, skills, risks, and opportunity areas.
Define the roadmap, architecture, operating model, controls, use-case portfolio, and capability plan.
Engineer AI agents, RAG systems, data pipelines, software applications, integrations, automations, and platforms.
Validate quality, risk, security, governance, compliance, performance, and production readiness.
Equip internal teams with runbooks, standards, training, operating discipline, and ownership models.
Insights
Who we are
Captivolt is built by practitioners who understand what it takes to move AI from experimentation to enterprise production. Our work brings together AI engineering, software delivery, data foundations, quality assurance, governance, security, and capability transfer — so clients get practical systems, not theoretical advice.
We design and build AI agents, RAG systems, copilots, automation workflows, and AI-native applications that work with enterprise systems and data.
We validate, monitor, govern, and evidence LLM, RAG, and agentic systems before and after production release.
We connect AI to APIs, cloud platforms, data layers, systems of record, DevOps pipelines, and operational workflows.
We help internal teams adopt, operate, and improve AI systems through playbooks, standards, training, and runbooks.
Start with a structured conversation or use the AI Readiness Diagnostic to identify where your organisation should begin.