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Team Builder

Requirements in. Client-ready teams out.

Describe the project, paste the requirement, or upload the RFP. Team Builder returns a fully staffed, ranked team, tuned to whichever cost-versus-coverage trade-offs make sense for the engagement. You pick what reaches the client.

Create new requirement Create Set up your project requirements here, add as many details as possible to get the best matches from internal and external resources. Don’t worry, you can always modify this later. Project title Data Scientist for Regulatory Start date # of resources Client Location 2025/12/12 Large Bank New York 1 Requirement detailsFocus on skills, experience, certifications and education. Be as detailed as possible to get the best results. Mandatory requirements- Mandatory requirements- Proven experience in Java and Python programming languages.- Strong understanding of SQL and data management practices.- Experience with machine learning frameworks, particularly PyTorch.- Knowledge of embedding techniques and their application in data science.- Familiarity with AWS cloud services and deployment strategies.Skills- Strong problem-solving skills to address complex technical challenges.- Ability to work effectively in a collaborative team environment.- Excellent communication skills for clear articulation of technical concepts.- Attention to detail in code and data processing
Detailed AI match reports and scoring

Speed and fit are the same race.

The firm that responds quickly and effectively is usually the one that wins. The challenge is that the data needed to assemble that team. Skills, availability, rates, clearances, lives across several systems, which is what makes the email thread a necessity in the first place.

Client Requirement Senior Cloud Architect Lead Healthcare EU-based AWS + Azure Industry Location Required 6 Month Engagement Timing
Days 0 1 2 3 4 Firm A(EmailThread) Firm B(LegacyPSA) Firm C(LumiereTeam Builder) 5 6 7 8 9 10 ProposalSent ProposalSent ProposalSent

Same requirement. Same talent pool. Different speed to credible team.

From requirement to proposed team.

Step 1

Drop in the requirement. A JD, an RFP, an email thread, or a form. Team Builder parses roles, skills, dates, locations, rates, and constraints.

Requirement detailsFocus on skills, experience, certifications and education. Be as detailed as possible to get the best results. Mandatory requirements- Mandatory requirements- Proven experience in Java and Python programming languages.- Strong understanding of SQL and data management practices.- Experience with machine learning frameworks, particularly PyTorch.- Knowledge of embedding techniques and their application in data science.- Familiarity with AWS cloud services and deployment strategies.Skills- Strong problem-solving skills to address complex technical challenges.- Ability to work effectively in a collaborative team environment.- Excellent communication skills for clear articulation of technical concepts.- Attention to detail in code and data processing Create Enrich
Filtered consultant list

Step 2

Lumiere reads your consultants. Skills, certifications, prior engagements, availability, rate, location, languages, clearances. Not keyword matching — a multi-factor read of who would actually be best fitted for the job.

Step 3

Get a ranked team. A primary team plus alternates per role. Each name: match score, reasoning, availability, rate. Override anything, the system learns from your decisions.

Detailed consultant matching

Drill into each candidate with a Match Report - skill scores and named gaps. For unfilled seats, Lumiere drafts a JD to find the candidate in the market.

Send to proposal

Detailed AI client reports

Where it earns its keep: complex programs.

A 31-role transformation across regions, three rate tiers, clearances on five seats. Read as one requirement, returned as one coherent team. Not 31 searches stitched together. One read, one team, one shortlist.

Complex AI team builder

Faster than the competitor. Better-matched than the email thread.

On average, customers cut the time from requirement-received to client-ready shortlist by 85%. The match quality, measured by client acceptance and engagement health twelve months in, runs around 67% above the email-thread baseline. Faster proposals, better-suited consultants, fewer engagements that go sideways at month four.

Cost vs coverage. Your call.

Lumiere proposes the optimizations. You decide the trade-off.

Best cost.

The cheapest team that covers most skills. Any partial coverage is named explicitly. The right choice when budget is the binding constraint.

Full coverage, any cost.

Every skill in the requirement covered. Cost lands where it lands. The right choice when the engagement can't tolerate a skill gap.

Anywhere in between.

One slider. Names, costs, and coverage move with it. Every trade-off visible before you commit.

AI scoring and team builder

When no internal name fits.

If a role on the project has no qualified consultant on your bench, or if the best match is a 60% match, Lumiere flags the gap, drafts a post-ready JD against your firm's templates, and routes the requirement to your hiring pipeline. The proposal still goes out on time, with the gap addressed proactively.

Project Director

Consultant

Data Engineer Lead

External

JD Drafting

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Sr Data Engineer

Consultant

Cloud Architect

External

JD Drafting

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Complance

Consultant

See Team Builder build a real team, your data, your trade-offs.

Twenty minutes with the Lumiere team. Bring your own requirement, and we'll show Lumiere's Team Builder in action.

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