VegradeAI engineering
Reference programs

Program shapes built for procurement scrutiny

Each entry is an illustrative engagement pattern — architecture, governance, evals, and target outcomes drawn from common industry shapes. We are pre-launch on named client references; specifics are shared under NDA when there is mutual fit.

Illustrative content. These are reference program shapes — not retroactive case studies of named Vegrade clients. Target outcomes are benchmarked against industry literature, not specific engagements.

Fixed outcomes

Statements of work tie to acceptance criteria — not open-ended staff aug. You know what you're buying before work begins.

Enterprise-ready artifacts

Security narratives, data flows, runbooks, and vendor questionnaire packs suitable for your procurement process.

Steering cadence

Weekly demos, written status readouts, and formal change control when scope shifts. No surprises.

Reference programs

Selected program shapes

Each deep dive includes architecture notes, governance controls, and target outcomes designed toward common industry patterns — not specific Vegrade engagements.

Legal technology8–12 week production program

Citation-backed M&A diligence RAG

Fixed SOW · security review pack included

Legal teams need defensible speed—answers must move quickly while remaining traceable to source spans. This program shape delivers a retrieval stack with explicit provenance, review SLAs, and eval gates so partners can trust answers under scrutiny.

Target outcome

60–80%

Reduction in first-pass review time vs. manual baseline—benchmarked against published RAG programs in legal-tech literature.

  • Offline relevance suite seeded from real failure modes—not toy benchmarks
  • Confidence tiers with mandatory human review below agreed thresholds
Next.jsOpenSearchpgvectorCross-encoder rerank
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Real estate6–10 week production program

Policy-bound outbound lead agent

Fixed SOW + 4-week hypercare

Real estate teams need velocity without brand risk. This program shape pairs a multi-step agent with deterministic business rules, evaluable generations, and operator tooling so marketing and ops can iterate safely as seasons and inventory change.

Target outcome

1.5–2.5×

Uplift in qualified tour bookings vs. a control cohort—based on comparable outbound-agent benchmarks.

  • CRM writes with idempotency keys and replay-safe webhooks
  • Daily eval reports on tone, compliance phrases, and conversion proxies
TypeScriptTemporalTwilioSalesforce APIs
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Customer experience8–12 week production program

Omnichannel support deflection agent

Phased SOW (pilot → production hardening)

Support organizations need deflection that does not erode CSAT. This program shape pairs automation with explicit escalation paths, human calibration loops, and operational dashboards so leaders can trust the system at scale—not chase anecdotal failures.

Target outcome

50–70%

Tier-1 ticket deflection at 30-day steady state—based on benchmark deployments with stable CSAT.

  • Shadow mode before customer-facing enablement
  • Online eval harness sampling production conversations
PythonFastAPIRedisVector store
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Your program

Recognize a pattern that fits your problem?

Tell us your outcome, constraints, and timeline. We'll map the closest program shape and share a written scope before you commit.