Win the bid.
Defend the work.
AI-powered workflows for federal contractors — auditable, framework-aligned, and defensible on a recompete.
Rigovera Staffing — deployed with an intelligence-community prime contractor
Platform Modules
One platform. Four modules.
Each module addresses a discrete federal contractor workflow — same governance posture underneath, same audit trail, same defensible output.
Rigovera Staffing
Get the right compliant people onto the contract.
Map a candidate's real experience against the contract's labor categories before you submit — so the resume you send is the one that survives the customer's review, not the one that comes back rejected.
- LCAT-to-resume compliance mapping with gap analysis
- Qualification gaps flagged before submission, not after a rejection
- Interview prep built from the specific gaps found
- Compliant, submission-ready resume output
Rigovera Capture
Decide which bids are worth your team's time.
Built for the cleared and IC work the SAM.gov-based tools can't see. Brings the evidence behind a go/no-go into one workspace — so you protect the pursuits that fit and make the defensible no on the ones that don't.
- An opportunity room that holds analyses, documents, teaming, and chat together
- A bid / no-bid recommendation shown as a clear Go, No-Go, or Conditional call
- Past conversations kept in a sidebar, each with a preview, so analysis is a thread you can return to
- On-demand analysis export to a working document — full analysis, incumbent, or teaming match — with a sources appendix
- List or Kanban pipeline views, with drag-to-move across stages
Rigovera Proposals
Strengthen the answer before it goes out.
An augmentation layer, never a generator. You write every word; Proposals surfaces your past-performance evidence, tests your answer against it, and shows you where the response is strong, where it's thin, and where you have a gap to address — across questionnaires, RFIs, and RFPs. It starts from a Capture opportunity, so the response is bound to the analysis behind the decision to pursue.
- A focused workspace that pulls obligations out of the solicitation and works them one at a time, with your evidence and your position side by side
- Past-performance evidence surfaced per obligation, ranked by relevance in plain weak / moderate / strong bands
- For questionnaires and RFIs: a read on where you stand, then what to include depending on how much you choose to disclose
- A test-my-thesis pass that takes an unpolished draft and returns how it may be perceived — positive and negative — never a score
- For RFPs: a read of what each requirement is really asking, an overlap check so a submission isn't over-reliant on one past-performance contract, and a per-requirement thought-partner chat with full access to your firm's documents
- Team comments with @mentions, kept separate from the analysis so collaboration never alters the evidence
Rigovera Roster
Keep the contract staffed for its full life.
Managing people across a portfolio of contracts — turnover, level changes, labor-category shifts, and the prime-to-sub balance every contract has to hold.
Being stood up.
Defensible records — LCAT crosswalks, qualification checks, and an audit trail — are built into every module, not bolted on.
We are actively transitioning our product brand from GovReadyAI to Rigovera. The platform, the team, and the mission are the same — the name better reflects where we are taking it.
Rigovera is architected as an umbrella platform with named modules. Staffing, Capture, and Proposals are live today; Roster is being stood up. Compliance isn’t a separate module — defensible records are built into every one.
Rigovera is implemented by Gittielabs when an Applied AI Diagnostic identifies workflows worth building on. Every deployment is auditable, framework-aligned, and defensible on a recompete.
Ready to Deploy
AI that survives a recompete.
Rigovera is not a pilot. It is a production platform built from the ground up for the audit trail federal buyers demand.
- Auditable by design — every AI action is logged and traceable
- Framework-aligned — NIST AI RMF, ISO 42001, TEVV out of the box
- Defensible on recompete — documentation built in, not bolted on
- Deployed in production — not vaporware, not a demo environment