AI opportunity and workflow design
Find the right first move by mapping the current workflow, bottlenecks, owners, systems, risk, volume, and expected value.
- Workflow and readiness assessment
- Use-case prioritization
- Governance and success criteria
SINQ Labs is a founder-led AI consulting partner in Tampa Bay. We deliver that consulting as an AI-native service: finished ops work via agents that run the workflow, with people approving anything that touches money, contracts, or HR, combining strategy, product, engineering, integration, and ongoing agent operations so the engagement does not stop at a roadmap or prototype.
What we work on
Every business runs on the same core functions. We map them into 8 families and 117 formulas, each a realistic AI agent workflow: it reads your systems, does the routine work, and reports back. Anything that touches money, contracts, or HR is prepared for a person to approve.
Strategy, implementation, and managed operations belong in one delivery loop. SINQ can enter at the point where your team is stuck and carry the work through launch.
Find the right first move by mapping the current workflow, bottlenecks, owners, systems, risk, volume, and expected value.
Build the system, connect it to existing tools and data, test it against real operating conditions, and prepare the team to use it.
Co-build a new application, platform, or business around a valuable workflow and a partner with domain knowledge or distribution.
Explore the Build partnership model →We deliver and run named agents into an existing workflow as a managed operating capability, bots that do the work, then monitor, maintain, govern, and improve them. ZoeOS is how we deliver.
Start with an assessment →Some workflows deserve a new product. Others need measurable operational help now.
Use this path when the workflow can become a differentiated product, platform, business line, or standalone company.
Use this path when a painful internal workflow needs speed, consistency, follow-through, and controlled execution.
A compact delivery loop keeps the business objective, technical implementation, and operating controls connected.
A short back-and-forth by text or email about how your week actually runs: the work, the tools, and the handoffs. We note where things slip and where there’s room to grow.
You get a clear summary in your own terms, ranked by the time and money at stake, both what’s leaking and what you could gain. You correct anything we got wrong.
A plan that matches each pain to SINQ Formulas, then a Partner Fit call with Peter to choose the path: co-build a product, or run agents inside what you already use.
We build your formulas into working agents inside your systems, governed by ZoeOS with scoped rules, escalations, monitoring and tuning. People approve anything that touches money, contracts, or HR.
The best first use case is usually not the flashiest. It is a narrow, painful process where better speed, consistency, or follow-through matters to an accountable operator.
Our portfolio applies the same workflow-first approach across industries where operational complexity creates a clear opening for AI.
Internal operating workflows where structured queues, policy checks, and exception handling can reduce manual coordination.
See SINQ Ops →Multi-agent workflows that organize document-heavy work and prepare structured outputs for professional review.
See Romina Day →Operational systems that improve visibility, handoffs, and execution across people, suppliers, and processes.
See Ontide →A disciplined command layer for early-warning intelligence, operational playbooks, ownership, and escalation.
See RapidGuard.ai →Agents for intake, reporting, follow-up, coordination, review, and other scoped internal workflows.
Start with an assessment →If the work is repetitive, measurable, and important enough to own, we can evaluate whether AI is the right next move.
Start your assessment →
SINQ Labs is led from the Greater Tampa Bay Area by founder Peter Quintas. We work directly with operators to understand the workflow, decide whether the right path is Build or Operate, and stay accountable through implementation.
Connect with Peter on LinkedIn →The practical questions to answer before an AI initiative moves into a real operating environment.
SINQ Labs is founder-led from the Greater Tampa Bay Area and works with Florida operators statewide when the workflow, ownership, and urgency are clear. Use this Tampa page for Bay Area consulting and implementation detail; see our Florida AI consulting page for statewide framing. For the Operate path (managed AI agents via ZoeOS), start with an assessment and Partner Fit call, or read how ZoeOS works on About.
AI consulting identifies the business problem, workflow, risks, and expected value. AI implementation turns that plan into a working system by building the solution, connecting data and tools, defining controls, testing it, and launching it into operations. SINQ Labs handles both so strategy stays connected to execution.
A strong first workflow is repetitive, time-sensitive, measurable, and owned by a person who can review exceptions. Intake, document review, reporting, follow-up, coordination, and reconciliation are common starting points.
Yes. AI agents can be designed to work with tools such as Google Workspace, Microsoft 365, CRM systems, project management platforms, support desks, forms, scheduling tools, billing platforms, APIs, webhooks, and automation services. The exact approach depends on access, data quality, and operating requirements.
Each agent should have a defined role, approved data access, operating rules, escalation paths, review checkpoints, and measurable outcomes. Higher-risk actions remain subject to human approval.
Use managed AI agents on SINQ's Operate path when an existing Tampa Bay workflow already has an owner and needs speed, consistency, and controlled follow-through now. Operate installs named agents into the tools and process you already run, with defined roles, approved actions, escalation paths, and ongoing monitoring - not a chatbot demo handed off after launch. Choose Build instead when that workflow can become proprietary software, a platform, or a commercial product. Start with a free assessment, then a Partner Fit call to scope Operate versus Build for that workflow.
Cost depends on workflow complexity, integrations, data readiness, risk, and whether the work is a custom application or a managed-agent deployment. Pricing is value-based and scoped to each engagement: start with a free assessment conversation with Zoe from SINQ Labs, then a Partner Fit call to scope the work. Custom applications and venture partnerships are scoped around the product and commercial opportunity.
A focused ZoeOS workflow can target first value in one to two weeks when access and ownership are clear. AI-native applications and ventures require a longer build cycle; SINQ's current Build model targets a pilot in roughly 60–90 days.
Bring one workflow that is creating manual overload, delays, inconsistent follow-through, or operational risk. Zoe from SINQ Labs will learn how it runs, and a Partner Fit call will determine whether the right next move is consulting, implementation, Build, or Operate.
We identify the owner, current process, urgency, systems, and business objective.
We decide whether the opportunity calls for consulting, implementation, an AI-native application, or managed agents.
We define the first release, owners, controls, integrations, metrics, and commercial structure.
One way to reach you is all we need. Everything else happens in the conversation.
Zoe from SINQ Labs will reach out to learn how your week works. If there’s a fit, she books a Partner Fit call to walk through the plan.