The Transformation

Before & After

What changes when your project management system actually learns from your work? Here's the same week at a 75-person agency, with and without Guildry.

Time to estimate
2-3 days→2-3 hours
Estimate accuracy
±30%→±15%
Retro completion
20%→80%
Case study turnaround
1-2 weeks→30 min
📥

New lead comes in

WITHOUT GUILDRY2-3 days

Scramble to respond

  1. 1.Founder gets email, forwards to sales lead
  2. 2.Sales lead asks around: 'Have we done something like this before?'
  3. 3.Someone remembers a similar project from 2 years ago
  4. 4.Dig through Google Drive for the old SOW (can't find it)
  5. 5.Ballpark the estimate based on gut feel
  6. 6.Send proposal, fingers crossed

No institutional memory. Every estimate starts from scratch.

WITH GUILDRY2-3 hours

Informed response in hours

  1. 1.Lead captured automatically from email or form
  2. 2.AI surfaces: '3 similar projects found, averaging 320 hours, 12 weeks'
  3. 3.One-click to see what went well/poorly on those projects
  4. 4.Generate SOW draft with realistic phases and estimates
  5. 5.Review, adjust, send

Powered by: Scout + Blueprint + your project history

📐

Scoping a project

WITHOUT GUILDRY4-8 hours per SOW

Educated guessing

  1. 1.Open a blank doc or copy an old SOW template
  2. 2.List out phases and deliverables from memory
  3. 3.Estimate hours based on... vibes?
  4. 4.Add 20% buffer (or forget to)
  5. 5.Realize you forgot a phase after the contract is signed
  6. 6.Absorb the overrun

Estimates don't improve over time. Same mistakes, different project.

WITH GUILDRY1-2 hours per SOW

Data-informed scoping

  1. 1.Describe the project in natural language
  2. 2.AI suggests phases based on your historical patterns
  3. 3.See confidence intervals: 'Design phase: 40-60 hrs (based on 8 projects)'
  4. 4.AI flags: 'Projects with this client tend to run 15% over. Adjust?'
  5. 5.Generate SOW with realistic numbers

Powered by: Blueprint + EstimationModel + Retro data

👥

Staffing a project

WITHOUT GUILDRY3-5 days to staff

Mental Rolodex

  1. 1.PM asks: 'Who's free in March?'
  2. 2.Ops lead checks spreadsheet (last updated... when?)
  3. 3.Email blast to contractors: 'Anyone available?'
  4. 4.Wait 48 hours for responses
  5. 5.Realize your best React dev is already booked
  6. 6.Compromise on fit or delay the project

No real-time visibility. Staffing is reactive, not proactive.

WITH GUILDRYSame day

Smart matching

  1. 1.Project skills auto-extracted from SOW
  2. 2.AI shows: 'Based on skills needed, here are 4 matches'
  3. 3.See availability, rate, and past project performance
  4. 4.One click to hold time on their calendar
  5. 5.Contractor gets a brief: here's what the project is, here's the context

Powered by: Bench + Blueprint integration

📊

Mid-project check-in

WITHOUT GUILDRY2+ hours/week in meetings

Status meeting theater

  1. 1.Weekly status meeting (30 min, 6 people)
  2. 2.PM manually compiles hours from time tracker
  3. 3.Compare to... what was the original estimate again?
  4. 4.Client asks 'Are we on track?' You're not sure.
  5. 5.Scope creep happens but nobody documents it
  6. 6.Find out you're over budget when it's too late

No early warning system. Problems surface at the end.

WITH GUILDRY15 min/week async

Continuous awareness

  1. 1.Dashboard shows: estimated vs actual in real-time
  2. 2.AI flags: 'Design phase at 80% of budget with 60% complete'
  3. 3.Scope drift detected: 'Client requested X, not in the original SOW'
  4. 4.Auto-generated status update ready for client review
  5. 5.Course-correct while there's still time

Powered by: Relay + time tracking integration

✅

Project closes

WITHOUT GUILDRYRetro skipped 80% of the time

On to the next one

  1. 1.Project ends (or fades out)
  2. 2.Retro scheduled but keeps getting pushed
  3. 3.If it happens: vague notes, quickly forgotten
  4. 4.Lessons learned doc goes to Google Drive graveyard
  5. 5.Next similar project: repeat all the same mistakes

Learning never compounds. Year 5 isn't smarter than year 1.

WITH GUILDRY15-minute conversation

Learning captured automatically

  1. 1.AI drafts retro from project data: 'Design ran 20% over. Extra revision rounds.'
  2. 2.Quick conversation: 'Was that a client issue or scoping miss?'
  3. 3.Insights feed back to estimation model
  4. 4.Next similar project gets better defaults
  5. 5.Case study draft generated for sales

Powered by: Retro + Proof + learning loop

📝

Sales needs a case study

WITHOUT GUILDRY1-2 weeks (or rushed overnight)

Start from scratch

  1. 1.Sales: 'Do we have a case study for fintech projects?'
  2. 2.Marketing: 'I think we did one in 2019...'
  3. 3.Find the old PDF. It's outdated and generic.
  4. 4.Ask the PM to write something new (they're busy)
  5. 5.Cobble together a deck the night before the pitch

Sales collateral is always stale. Good work never gets packaged.

WITH GUILDRY30 minutes

Case studies on demand

  1. 1.Ask: 'Generate case study for fintech projects'
  2. 2.AI pulls: project details, outcomes, metrics, testimonials
  3. 3.Draft tailored to the prospect's industry and concerns
  4. 4.Review, approve, send
  5. 5.Prospect gets relevant proof, not generic marketing

Powered by: Proof + project history + Retro outcomes

The Compound Effect

📊

Project 1

System uses industry defaults. Estimates are reasonable but generic. After delivery, first retro feeds the model.

📈

Project 10

Model knows your patterns. "Your design phases tend to run 15% over" becomes actionable. Estimates improve.

🎯

Project 50

Competitors can't replicate your estimation accuracy. Your data is your moat. New hires onboard faster with institutional knowledge.

This is the learning loop. Every project makes the next one easier. The system gets smarter whether you're paying attention or not.