Optimize Consultant Staffing with a Custom AI Allocation System

Most 20-person consulting firms run their operations on a master spreadsheet. This schedule is often supplemented by project management tools like Asana or HubSpot Projects, but the core allocation logic lives in Google Sheets. These tools can track who is assigned to a project, but they cannot intelligently recommend who *should* be assigned based on skills, current utilization, or profitability.

In practice, this creates a significant bottleneck. When a new project is won, an operations manager or partner opens the master spreadsheet. They see who appears to be available, but this view lacks critical context. To make a decision, they must mentally cross-reference consultant skill sets, seniority levels, and who might be nearing burnout. This often involves multiple Slack messages to other managers, turning a single staffing decision into a time-consuming coordination exercise.

The structural problem is that spreadsheets and project management tools are not built for optimization. They are static databases that lack a constraint model. They cannot understand business rules like, "a team requires one partner and two analysts," or "prioritize staffing for projects with margins over 40%." These critical rules live in a manager's head, making the process dependent on a single person and impossible to delegate or scale effectively.

The engagement would begin with a data systems audit. Syntora would connect to your time-tracking system, such as QuickBooks Time, and your CRM or project tool, like HubSpot, to build a unified history of every project. This audit maps project durations, team compositions, required skills, and financial outcomes. The result is a clear report on your firm's data quality, identifying what is reliable for modeling and what requires cleaning.

The core of the system would be a constraint optimization model, built using Python libraries and wrapped in a FastAPI service. This model ingests your project pipeline and current consultant availability as inputs. It then generates a staffing plan that maximizes a defined objective, like billable utilization, while respecting all your business rules. Consultant data and project assignments would be managed in a Supabase database, providing a stable source of truth.

The final deliverable is a simple web interface showing the recommended staffing plan for the next six weeks, highlighting potential conflicts or underutilized staff. The system can push assignments back into your project management tool, fitting into your existing workflow. You receive the full source code, a runbook for updating rules, and a system deployed on AWS Lambda for an operational cost under $50/month.