Built for your workflows
We learn your systems, tools, judgment calls, handoffs, and approval needs before we build.
We build custom AI agents and software for the work your team needs done.
Give your team more capacity for higher-value or revenue-generating work. We start with your workflows and keep people in control of key decisions.
We build the AI agents and software infrastructure around your proven workflows, so your team can take on more as the business grows. We agree on a baseline, measure the work, and keep your people in control.
We learn your systems, tools, judgment calls, handoffs, and approval needs before we build.
We agree on access, ownership, and approval boundaries. Supported cloud models may process prompts when selected.
Agents retain approved company knowledge, learn from corrections, and improve through controlled refinements. As AI models improve, the best supported options can plug into your existing setup.
Turn suitable computer work into governed AI workflow automation. We define the baseline with your team, measure what changes, and keep people in control of consequential actions.
We identify the highest-leverage use cases across your organization, with your team’s input.
We build custom agents and/or software to your team’s specifications and workflows.
We hand off the agreed infrastructure, teach your team to use it effectively, and refine it together.
Coming soon
Integrates with 1000+ tools
Runs on 100+ LLMs
A Jarvis-style assistant delivers one executive briefing, organizes priorities, prepares decisions, delegates follow-through, protects approvals, and keeps leadership informed.
One responsible service lead can oversee a much larger inbox while agents organize context, triage requests, draft replies, route exceptions, and prepare repetitive service work.
Turn company-specific workflows into practical internal software with agent-assisted development and governed human review.
Turn approved source files into ready-to-edit branded content while your people retain the company voice and final approval.
Monitor ad comments, reviews, policy changes, and content output, then flag potential issues for timely response and legal or compliance review.
Turn approved offers, brand rules, product files, and campaign learning into ready-to-review static ad concepts and variations.
Build additional company-specific agent systems for suitable workflows, with team training and controlled ongoing refinement.
It is a company-specific system of custom AI agents, business context, tools, permissions, and human approvals. CoreAgentic builds it around your selected workflows rather than installing a generic chatbot.
One AI assistant handles a conversation or task. An agentic department coordinates specialist agents across defined workflows, while people keep approval over consequential actions.
CoreAgentic works with established companies and enterprise teams that have proven operations, repeatable computer-based work, and decision makers who want measurable operational value from carefully governed automation.
We agree on ownership, access, and handoff terms for each engagement before work starts. Your team receives the agreed infrastructure and training.
No. The solution can use supported cloud models, which may process prompts. We map data flows and provider choices with your team before building.
ChatGPT is useful for occasional questions. A CoreAgentic department uses your company’s approved context, workflows, permissions, and persistent knowledge so it can work inside defined processes with clear controls.
An internal build can be a good fit if your team has the time, expertise, governance discipline, and long-term maintenance capacity. CoreAgentic offers a defined alternative when you do not want to carry that work alone.
AI can make mistakes. We evaluate workflows, limit what agents can do, and require human approval where consequences matter. Outputs can be checked, and uncertain work can be escalated.
Protection depends on the chosen architecture. We map data flow, isolation, model providers, retention, permissions, and deletion before building. Supported cloud models may process prompts when selected.
Every engagement is scoped around the selected workflows, controls, and implementation needs. Commercial terms are provided after discovery and scope definition.