Large GovCon firms have dedicated pricing departments, market intelligence subscriptions, and BD analysts whose only job is tracking opportunities. Arcvue gives every firm those capabilities—built on your actual cost structure, connected to live market data, without the manual workflow overhead that makes pricing feel like a second full-time job.
Every GovCon firm that prices seriously has a pricing model. The model is usually good. The workflow around it is where the time goes—and where the errors come in.
Here is what the pricing workflow looks like today. Someone saves a copy of the master Excel file for this bid. They manually add the positions specific to this RFP. They manually enter the vehicle rates and LCATs from a separate source. They enter the indirect rates from wherever the current version lives. The model produces numbers. Finding the formula that drives a specific output means pressing F2 on cells until you locate it. When assumptions change, the version you edited and the version someone else edited need to be reconciled. Version control is whoever saved last.
Arcvue replaces that workflow—not the quality of the underlying model, but all of the overhead surrounding it. Vehicle rates and GSA schedule LCATs are pre-loaded and maintained in the platform. Indirect rates pull nightly from your actual ERP cost pools—no manual entry, no question of which version is current. Assumptions are versioned automatically. The audit trail is built in—every derivation is transparent in the interface, not traced by pressing F2. When submission comes, the pricing audit walks through compliance checks and produces a formal attestation with digital signoff.
Contract vehicle libraries carry your ceiling rates for GSA MAS, OASIS+, and other vehicles. Each position maps to the correct Labor Category Alignment Tool entry so LCAT matching reflects how GSA actually classifies the work—not just job title similarity. Ceiling rate headroom is visible at the position level so you know exactly how much room you have before you hit the GSA cap.
Market intelligence from GSA CALC+ shows where your rates sit relative to competitors billing the same labor categories on similar contracts. This is a validation layer against the pricing you've already built from your cost structure—not a substitute for it. You price from cost. You validate against market.
Incumbent rates are pulled directly from USAspending.gov contract obligation data. Look up any predecessor contract by PIID or recipient name, compare incumbent rates against your proposed rates position by position, and see exactly where you stand before you submit. On a recompete, this is the most important data point in the proposal.
Before submission, the pricing audit walks through a structured compliance review—contract-type-specific questions, a system comparison that flags discrepancies between your stated assumptions and what the numbers show, and a formal attestation with digital signoff for submission-grade proposals. Not a compliance stamp. A governance process that makes sure pricing and leadership are aligned on what's being submitted and why.
A pipeline is only useful if it's measured against something. Most BD tracking tools tell you what's in the pipeline. Arcvue tells you whether it's enough—against your actual growth targets, broken down by division, year by year across the forecast horizon.
Every opportunity is tracked as binary. You win it or you don't. Probability weighting is available as a sanity check for management purposes, but the coverage ratio the platform reports uses unweighted pipeline—because in GovCon, a 40% PWIN opportunity doesn't produce 40 cents on every dollar. It produces either the full contract or nothing. A coverage ratio built on weighted pipeline overstates your real position and understates the work you need to do.
Coverage ratios are computed by division and by year, against the growth assumptions embedded in your contract waterfall. When Federal Health needs $4.2M of new contract wins in FY27 to hit its number, the platform tells you exactly how much unweighted pipeline in that division covers that target—and whether the current pipeline is 2x, 5x, or 12x coverage. Low coverage in a specific division and year surfaces early enough to do something about it. High coverage in one division can't mask low coverage in another.
Opportunity tracking captures the information that actually matters for a GovCon BD pipeline: agency, contract vehicle, set-aside type, estimated value, period of performance, anticipated award date, incumbent, and stage in the pursuit. Each opportunity is assigned to a division and tagged to the year it would produce revenue. The pipeline feeds directly into the contract waterfall and the scenario planner so a specific opportunity can be modeled as won or lost without rebuilding anything.
BD performance in most GovCon firms is tracked in a spreadsheet someone updates when they remember to. Win rates are approximated. Competitive positioning is based on institutional memory. The data that would sharpen every future bid decision exists somewhere—in emails, in proposal files, in someone's notes—but it's never aggregated into a usable form.
Arcvue's win/loss tracker pulls every submitted bid automatically from the pricing tool. When a proposal is marked submitted, it enters the bid history record. When the outcome is known—win or loss—it's recorded against that record along with the competitor awarded, the winning rate if known, and any notes from the debrief. The record builds without anyone maintaining a separate tracking spreadsheet.
Win rate analysis runs against every meaningful dimension: by agency, by contract vehicle, by set-aside type, by division, by LCAT category, by price range. The CGO can see which agencies the firm wins most consistently, which vehicle types produce the best win rates, and where the firm is competitive on price versus where it's consistently above market. That's the data that informs pursuit decisions, pricing strategy, and where to invest BD resources—produced from the actual bid history, not from memory.
Competitor rate intelligence accumulates over every bid. When the same competitor appears across multiple losses, their rates by LCAT build into a profile over time. The CALC+ market intelligence is a point-in-time snapshot. The bid history is a longitudinal record of what competitors are actually winning at, in the markets and vehicles where your firm competes. That institutional knowledge lives in the platform, not in the head of whoever ran the last BD review.
Every GovCon firm has a past performance document. After a few years it runs to hundreds of pages, crashes when you open it, and requires Ctrl+F and Next, Next, Next to find anything. When a proposal requires specific citations, the team spends hours searching a document never designed for search.
Arcvue replaces that document with a structured database where every past performance record is searchable by every field that matters: agency, NAICS code, contract vehicle, dollar value, period of performance, work type, and labor categories staffed. Finding every HHS contract you've performed involving data analytics that staffed program analysts is a filter selection, not a document search.
AI ingestion reads your existing unstructured past performance documents—Word files, PDFs, legacy write-ups—and extracts structured records from them. You don't manually re-enter years of history. You upload what you have. The platform reads it, pulls the relevant fields into structured form, and flags anything that needs human confirmation. The 500-page document that crashes on open becomes a searchable database overnight.
For each proposal, export only the fields you need for that specific RFQ—not a full dump of every record, but a formatted output with the exact columns the proposal requires, drawn from the records you select. Filter by relevance, select the matching records, select the export fields, get a clean formatted document. No reformatting. No copy-paste from a document still open in another window. Capability assertions on each record connect past performance to solicitation scoring—opportunities are matched against what you've actually delivered, not a capability statement someone last updated two years ago.
SAM.gov and eBuy post hundreds of new solicitations every day. Monitoring them manually means either reviewing everything—which is a full-time job—or applying keyword filters that miss relevant opportunities and surface irrelevant ones. Neither approach scales.
Arcvue monitors SAM.gov and eBuy daily and processes every new posting through a three-tier scoring model. The first tier applies fast rule-based filters—set-aside type, NAICS code, dollar threshold, agency—to eliminate obvious non-fits before anything else runs. The second tier applies AI-based matching against your capability profile. The third tier runs a deeper relevance assessment against your actual past performance records, scoring the opportunity against contracts you've actually won and performed.
The scoring model isn't matching against keywords you defined. It's matching against your actual delivery history—the agencies you've served, the work types you've performed, the contract vehicles you hold, the labor categories you've staffed. An opportunity that looks like your HHS CMS Quality contract scores high because your past performance says you can do that work. An opportunity that looks like nothing you've ever won scores low regardless of how the solicitation is worded.
Scored opportunities flow into three buckets in the BD module. Pursue-or-decline decisions for opportunities that scored high and are fully biddable. Market intelligence for opportunities that are relevant but not yet in a state to bid—sources sought, RFIs, pre-solicitation notices—tracked for awareness. Filtered out for everything that didn't clear the threshold, with the ability to rescue a specific opportunity if the BD team disagrees with the score.
M&A analysis, earnout modeling, lender model export, and debt financing—all against your actual operating baseline.