Autonomous agents that reason, plan, and act.
We design enterprise AI agents that handle multi step work end to end, pulling data from your systems, making decisions against your rules, and executing actions across CRMs, ERPs, ticketing tools, and internal APIs. No human in the loop required.
Built for real work,
not demos.
Our agents don't just answer prompts, they reach into your systems, reason over real data, and execute concrete actions. Every capability below ships with monitoring, guardrails, and a human in the loop fallback you can switch on.
Multi Step Reasoning
Agents plan a sequence of actions, evaluate intermediate results, and self correct when something doesn't match expectations.
Tool & API Use
Native connectors for Salesforce, HubSpot, Slack, Jira, SAP, Zendesk, Postgres, and any REST/GraphQL endpoint you expose.
Long Running Memory
Persistent context across sessions, accounts, and threads so the agent picks up exactly where the customer or workflow left off.
Guardrails & Policy
Approval gates, write action allowlists, and audit trails for every decision, so legal, security, and ops sign off without friction.
Multi Agent Orchestration
Specialist agents that coordinate, one researches, another drafts, a third executes, with a planner managing the handoff.
Observability Built In
Trace every reasoning step, tool call, and token spend. Drift detection and replay tooling come standard, not as add ons.
From idea to deployed agent.
Four stages, no surprises. Most engagements ship a working agent in production within six to eight weeks.
Workflow Mapping
We sit with the team that does the work today and map every decision, system touchpoint, and edge case the agent will need to handle.
Architecture & Tools
We pick the right model, scope tool access, and design the prompt and memory architecture, delivered as a clear technical spec.
Sandboxed Pilot
The agent runs in shadow mode against real traffic for two weeks. We measure accuracy, escalation rates, and cost per task before going live.
Production & Iterate
Phased rollout with kill switches, monitoring, and biweekly tuning. We hand over runbooks and stay on for ongoing support.
Questions about
Enterprise AI Agents
A chatbot replies. An agent acts. Our enterprise agents plan multi step work, call your APIs, write to your databases, and verify the result, closing the loop on a task instead of just answering a question about it.
You'll see a working prototype inside two weeks. Most teams reach a sandbox pilot in four to six, and full production rollout in six to ten, depending on integration complexity and approval gates on your side.
Every agent ships with a policy layer: action allowlists, dollar value approval gates, rate limits, and a human in the loop fallback you can flip on per task. Plus full audit trails for every decision the agent makes.
Whatever fits the job. We work across Anthropic, OpenAI, Google, and open source models, and we're routinely model agnostic in the architecture, so you can swap providers later without a rewrite.
Yes. We deploy into AWS, GCP, Azure, and air gapped on prem environments. For regulated workloads, see our on premise AI offering.
Stop experimenting.
Start deploying AI that works.
Book a free discovery call. We'll map your use case, scope a working prototype, and tell you honestly whether AI is the right tool for the job.
info@croncore.com