CelerBY LANDING POINT

September Search Partners
Discovery readout · September 2026

CELER

AI Roadmap

CELER
AI Roadmap

// What we set out to learn

Find the shortest path to a better search process.

The goal of our discovery was to understand how SSP manages a search today, how the team moves through its procedures, how SSP can achieve the Quick Wins SSP identified, and what the path to its long-term AI goals looks like.

Four questions shaped the work

  1. How does work actually move?

    Understand the real search process across OneNote, Ezekia, email, files, and interviews.

  2. Where can AI help first?

    Identify low-friction opportunities from the AI Opportunities deck that can create immediate relief.

  3. What is a capability gap?

    Separate missing functionality from usability, workflow, training, and adoption issues.

  4. What should SSP do next?

    Recommend a practical first phase while preserving a path to a shared AI workspace.

// What discovery revealed

The challenge is less about missing features.

The operating reality

  1. Ezekia is not in the natural workflow

    It often feels like an additional burden rather than the place where the work happens.

  2. OneNote works today

    The team has built a workable habit around it, but the information is harder to structure, share, and use as AI context.

  3. Bridget is a force multiplier

    The process currently relies heavily on one highly efficient coordinator, creating a continuity and capacity risk.

  4. Scale requires repeatability

    SSP needs procedures that preserve judgment and service quality without requiring another Bridget for every increase in volume.

// Option 1

Start with the work the team already feels.

These are practical applications of the quick wins identified in the AI Opportunities deck. They reduce repetitive work without asking SSP to change its entire operating model first.

01

Prompt library

Approved prompts for assessments, drafts, summaries, kickoff questions, progress agendas, and interview briefs.

02

Automated first drafts

Candidate, client, interview, and search materials prepared quickly and reviewed by the team.

03

Interview note summaries

Organize notes into strengths, risks, gaps, and follow-up questions.

04

Standardized assessments

Apply a consistent structure across candidates and searches without removing recruiter judgment.

05

Resume logo stamping

Automate a simple, visible task that currently consumes time and creates avoidable manual steps.

06

Document Design Studio

Optional add-on for creating branded documents through a dedicated design workflow.

// Future-state option · approximately $20,000

Build the SSP Workspace.

The working demo shows a dedicated AI workspace that brings search context, notes, files, CRM information, and interview coordination into a simpler experience. This would function as an experience layer around Ezekia, not a replacement for capabilities Ezekia already provides.

Give each search a shared workspace for notes, files, prompts, assessments, summaries, and next actions.

Make relevant candidate, client, assignment, and CRM context easier to access without forcing the team to navigate multiple systems.

Track interview requests, confirmations, calendar steps, and feedback so another colleague can take over without relying on Bridget’s memory.

Option 2 requires more setup and process definition. The scope should specify what remains in Ezekia, what lives in the workspace, and how the two systems stay synchronized.

Open the working demo ↗

// Recommended path

Learn while we improve.

Option 1 lets SSP capture value now and generate evidence about what the team actually needs next. Option 2 remains available if SSP decides it needs a simpler, shared experience around the search process.

Recommended sequence

  1. Launch the Option 1 quick wins, including the prompt library, Copilot workflows, resume logo stamping, and MCP write-back test.
  2. Re-engage Ezekia on training, configuration, and practical adoption of capabilities already available.
  3. Measure time saved, consistency, data capture, and the ease of handing off a search.
  4. Use those results to decide whether SSP needs the dedicated workspace shown in Option 2.

// Decision after the first phase

If Ezekia becomes easier to use and the quick wins relieve the team, continue improving the existing stack. If the team still needs a shared AI-native experience, proceed with the SSP Workspace.

// At a glance

What each option covers

NeedOption 1Option 2
Immediate AI quick winsPrompt library, drafts, summaries, assessmentsIncluded in a shared workspace
Resume logo stampingIncluded as a practical automationCan be included in the workspace workflow
Notes returned to EzekiaVia MCP connector, pending validationDefined through the workspace and integration scope
Ezekia training and adoptionParallel workstreamImportant foundation for the workspace
Shared search workspaceNot includedCore capability
Main tradeoffLower change, but keeps more fragmentationMore setup, process definition, and investment

Option 1 is the recommended first phase. Option 2 is approximately $20,000 and would follow a defined scope.