AI agents that do the work
We design task-specific agents that can research, draft, route, update systems, call tools, and hand off to humans when judgment is required.
- Workflow agents
- Tool-calling assistants
- Human-in-the-loop review
AI agents • knowledge bases • integrations • agentic products
We build AI systems that understand your business and get work done.
Hive Forensics AI builds production-grade agents, RAG knowledge bases, internal copilots, and custom integrations for companies that want AI embedded into real operations — not another demo that dies in a slide deck.
Agent strategy
RAG architecture
Product engineering
agent-command-center.app
Knowledge base
Find policy, contract, and SOP answers with source citations.
Agent action
Create ticket, update CRM, draft email, notify Slack.
Guardrails
Permissions, audit logs, evals, escalation rules.
Result: one secure AI layer over your people, data, and tools.
What we actually build
AI that is connected to your knowledge, tools, and workflows.
Knowledge bases employees trust
We turn scattered documents, tickets, SOPs, PDFs, and database records into searchable RAG systems with citations, permissions, and feedback loops.
- Document ingestion
- Retrieval tuning
- Role-based access
Agentic product development
We build the full product around the AI: dashboards, auth, APIs, billing, admin controls, queues, monitoring, and clean user experiences.
- SaaS apps
- Internal portals
- Production infrastructure
Integrations across your stack
We connect agents and knowledge systems to CRMs, ERPs, inboxes, calendars, spreadsheets, databases, and custom APIs so automation actually moves the business.
- API integration
- Data pipelines
- Automation triggers
Why clients hire us
Replace AI confusion with shipped business outcomes.
We focus on the useful layer: the agent, knowledge base, integration, workflow, and product experience your team will actually use.
✓Reduce support and operations backlog
✓Give teams one accurate place to ask questions
✓Automate repetitive research and reporting
✓Ship AI features customers can understand and use
✓Keep data private with permission-aware design
✓Measure quality with evals, logging, and review queues
Delivery process
From messy idea to operational AI product.
01
Map the work
We identify the workflows, data sources, tools, risks, and success metrics that matter.
02
Prototype the agent
We build a working slice quickly: retrieval, prompts, tool calls, guardrails, and UX.
03
Integrate systems
We connect the agent to your apps and data with authentication, permissions, and audit trails.
04
Launch and improve
We deploy, monitor, evaluate responses, tune retrieval, and add automations as adoption grows.
Ready to build?
Tell us what your team needs AI to do.
Bring the workflow, data sources, pain points, and tools. We will turn it into an agentic product plan and a build path.
OpenAINext.jsReactNode.jsVector searchPostgresAPIsCRMsERPsZapier/MakeCloud or private deployments