Real AI implementations, with real numbers.

A HIPAA-conscious chatbot customized per practice, in both text and voice.

• 400+ hours a month of patient-education time saved (projected)
• Whisper speech-to-text and Eleven Labs voice, tuned per practice

An LLM pipeline built for interpretability, so compliance teams can audit every flag.

• Materially improved MNPI detection accuracy
• Chain-of-thought reasoning gives audit-ready decisions

A structured discovery audit that turned fragmented operations into a costed AI roadmap.

• $1M+ in estimated savings identified
• 6 AI automation opportunities mapped with roadmaps

Embedding-based search over the brokerage's full training library, with source links.

• 80%+ reduction in agents' content-search time
• 100GB+ of training video and blog content indexed

Role-based retrieval with hallucination guardrails that fall back deterministically.

• 700 pilot users; 1,600 questions answered in two weeks
• Parent-document retrieval and query expansion bridge wording gaps

A structured 5-pillar assessment run as technical interviews with the target.

• Covers data, governance, modeling, testing and scale
• Findings report with positive and negative technical flags

A financial-language-tuned chatbot embedded directly in the existing FIS DX data room.

• 60+ hours a month saved for the fundraising team
• Source-linked answers with auto follow-up questions for LPs

A 14-chain LLM pipeline that replicates human compliance review, with a feedback loop.

• Flags inlined directly into source marketing PDFs
• Reviewer feedback loop continuously improves detection

A chatbot trained on IRS R&D code and TaxTaker's process, wired to Gusto for live eligibility.

• 30% less time on unqualified prospects
• Close rate up ~10% via self-serve eligibility

Criteria-filtered monitoring plus GPT-4 personalized applications, built in ~8 weeks.

• 80%+ time reduction on applications; 65% more interviews
• 24/7 Playwright automation against Bubble's job board

Photo-to-avatar generation with on-site badge printing as the lead magnet.

• 200+ high-quality leads at a single conference
• Vision-model trait extraction plus DALL-E 3 generation

Automated medical-condition hierarchy mapping instead of hand-built taxonomies.

• 1,000+ manual hours saved; 65,000+ active trials indexed
• Sub-5-second matching across 1M+ conditions

A two-stage pipeline splits fast preview from manufacturing-grade output.

1. Photo or prompt to a production-ready 3D mesh in minutes, 95% faster
2. ClipDrop cleans input; Hunyuan3D and NeuS2 build the HD model

A subscription RPA product rebuilt as a bounded, auditable agentic platform.

• Live in 21 of the top 30 US post-acute providers, millions of tasks/month
• Agents-on-reins + LLM doc comprehension run 5 RCM stages

Legacyleap read the legacy estate so the rewrite could start from a full map.

• 290+ VB6 stacks became one multi-tenant SaaS; rewrite cut 60%
• 3 AI products in 12 months; ~$500K+/yr licensing removed

Rebuilt a 15-system SAP sprawl into one governed, AI-ready platform.

• MigratiX agentic migration cut manual effort ~80%
• 50+ reports consolidated; reporting went quarterly to weekly

Decades of tribal knowledge and legacy data, made searchable behind one assistant.

• Unified layer spans ~400K orders, 10K customers, 4K products
• Expert playbooks surfaced in seconds, cutting lookup time ~75%

Prototyped as a custom GPT, then rebuilt on OpenAI's Agents SDK.

• One dispatch task now runs on $1.78/mo of tokens vs $11K/mo in salary
• Auto-triage flags new work orders against account, equipment, outage data

Regulated by design: straight-through for clean claims, human review for the rest.

• OCR + LLM extraction cut a 45-min task to ~12 minutes
• Confidence scoring sent edge cases to humans; scaled to new claim types

Grounded strictly in the brand's own content, with guardrails that escalate, not guess.

• 1,900 docs drive a 92% instant-answer rate, zero web content
• 4,000+ questions a month; sessions rose 5x post-launch

Voice AI replaced manual phone screening at a healthcare scale-up.

• Screens applicants within minutes of applying, then auto-books keepers with recruiters
• Pushes transcripts and sentiment to the ATS — time-to-hire 5X faster

A composite-key engine cleans dirty job data that defeated naive ingestion.

• PostgreSQL warehouse with row-level security replaced spreadsheets
• Defect and downtime now tracked at shift level, not monthly

Built on the plant's own sensor and CMMS data, surfaced in supervisors' existing routine.

• Daily failure-probability rankings cut downtime 14.2% to 8.7%
• $1.2M saved in year one; false positives down 40%

Trust is enforced per run, not per project: three layers gate each generation.

• Eval layer checks accuracy, PII-safety, and authorization each run
• Adversarial reviewer model flags inconsistencies before sign-off

Governance and audit trails were architected from inception, not bolted on.

• Natural-language layer returns consolidated answers with no SQL
• Company-level scoping keeps consolidation inside access limits

Grounded in Cando's own assessment history rather than generic retrieval.

• Automated drafts run at under $0.05 each
• Live voice capture freed 20+ expert hours per assessment

One reusable architecture, re-fit to each site's own data instead of rebuilt.

• Rollout fell from 6 weeks to 3 by the third plant
• Downtime dropped 14% to 8.8%, saving $2.7M a year

Auditability designed in: no code is final until it links to source.

• Three-model pipeline with human gates blocks hallucinated codes
• Every code traces to source chart text with confidence scoring

Retrieval-augmented generation grounded every recommendation in Superintelligent's own tool catalog.

• Embeds queries and retrieves matches from a Pinecone index
• Delivered hundreds of personalized tool recommendations

Five sequential agents split the work into classify, enrich, discern, and judge, each with confidence scoring.

• Categorizes 1–2M records a month at 85%+ accuracy
• Maps to a 10,000-category taxonomy in real time

A zero-write layer keeps the live ERP untouched while consolidating every domain.

• Read-only feed replaced scattered exports with one governed store
• Daily dashboards for volume, yield, and orders used by named owners

Research was deliberately separated from judgment to cut bias, mirroring how analysts actually work.

• Decision-ready trend reports in under 35 minutes
• About $3 per report, ~80% verdict consistency on re-run

Equivalence is proven with evidence, not assumed: production data drives it.

• Real production data replayed through legacy and migrated systems
• Regressions surface before cutover, hitting the ECC support deadline

A read-only agent with human review kept engineers in control of every change.

• Live metadata context drove up-to-10x faster configuration
• Temperature tuning (1.0→0.4) cut errors ~50%

A multi-agent design separated interviewing, drift detection, and evaluation to keep quality high at scale.

• Interviewed 150 employees in two weeks for $500
• Ran thousands of interviews in its first month live

Making the pipeline measurable came first; only then did targeted experiments improve it.

• Seven-metric evals cut endpoint hallucinations 26% to <1%
• Prompt caching cut cost ~25% (about $6) per run

A five-step workflow turns raw API docs into reviewable connector drafts, keeping a human in the loop.

• Crawls docs and pre-fills config — builds 10x faster
• Connector volume rose after the AI Assist launch

Sales and marketing systems unified to steer spend by LTV:CAC.

• Gong, Salesforce & HubSpot in one Connect environment
• Reverse ETL feeds LTV:CAC insights to ad platforms; lower cost/account

One reporting engine plus a CDP that activates audiences into ad platforms.

• Reverse ETL pushes custom segments to Meta & Google; sales +30%
• AskCorral AI querying alongside ROAS/conversion +39%, AOV +14%

Hundreds of disparate sources unified for non-technical staff.

• Tessitura, Delighted & the Explorer app in one analytics layer
• Staff self-serve NPS, donations and visitation drivers on demand

Fragmented e-commerce channels consolidated into one attribution view.

• GA/GA4 blending + attribution ties LTV:CAC to first product and campaign
• Unified reporting cut acquisition cost and lifted marketing ROI

Self-serve analytics for every team — no data-engineering hires.

• Mixpanel, AppsFlyer & GA unified into one governed reporting layer
• Reverse ETL flags churn-risk patrons and automates growth actions

A Phase 1 'Foundation' build paired brand and go-to-market groundwork with a lightweight AI layer.

• Visual identity, messaging, ICP and pricing validation delivered
• AI website chatbot qualifies leads, wired into a HubSpot CRM setup

A four-week 'Step Zero' study proved feasibility before any build was funded.

• Local vision models validated 98% accuracy, zero images sent to cloud
• 3 independent CIOs approved a 20-week roadmap across 8 systems

QuantFi ran a full unit-economics review for a fast-growing D2C wellness brand, building a fully burdened contribution-margin model across COGS, fulfillment, marketing, fees, returns, and CAC. It lifted gross margin 15%, cut wasted spend 20%, and raised EBITDA margin 20%.

QuantFi implemented NetSuite for a high-growth CPG brand running U.S.–Mexico warehouses, with multi-subsidiary, multi-currency operations and Shopify and 3PL integrations. It delivered 100% SKU-level visibility and cut the monthly close from 15+ days to under five.

QuantFi built a dynamic deal model for a PE sponsor underwriting a complex carve-out, flexing 15+ capital structures and three operating scenarios in real time with return waterfalls and a stranded-cost model. The sponsor went from LOI to a diligenced model in two weeks.

QuantFi turned an early-stage AI co-pilot startup's usage economics into an investor-grade financial model in under three weeks, designing hybrid subscription-plus-token pricing and 5+ capital-raise scenarios. The startup adopted token pricing pre-launch.

QuantFi ran a full sell-side process for a Midwest industrial business: an integrated 3-statement model, a Quality of Earnings review, and a banker-grade CIM. Normalizing earnings surfaced EBITDA 11% above management, and a curated M&A process drew 3+ LOIs in 90 days.

A sovereign clinical AI platform built where hosted AI APIs were legally off the table.

• 3 production AI products on one FHIR R4 engine, zero data egress
• 212 backend tests added and multiple security gaps closed

A top global venture firm made its scattered institutional memory queryable.

• Retrieval fell from weeks to seconds across years of firm memory
• 2 platforms unified 4 data sources; now trialed by the CEO

Lazer replaced a legacy Access system with an AI-native CRM.

• 100+ staff hours saved per month via automated document intake
• Hundreds of documents auto-ingested, parsed, and validated without human touch

Standardizing AI coding-agent deployment across a post-M&A codebase turned ad-hoc tool use into an org capability.

• PR review time down 20% across teams
• PR revert rate improved 65%, signaling higher quality

Lazer ran AI coding adoption as an engineering engagement, sequenced across 38 engineers.

• PR velocity up 40% within six weeks
• 13 external contractors offboarded, ~$300K/year saved per 10 engineers

A global consumer health company replaced ticket-based BI with self-serve agents.

• Kickoff to production in 21 days over three one-week phases
• 30+ brands in 60+ countries self-serve; ~20 workflows into one agent path

Lazer's discovery mapped a cross-functional packaging pipeline into a multi-agent design.

• Projected cycle: 16 weeks to 6 per SKU
• ~6,908 hours saved a year across 4,000 SKUs

A time-boxed pilot to prove document AI before a venture build.

• 80% accuracy on OCR-heavy insurance files where table-transformers failed
• Demo-ready prototype delivered in 6 weeks

Lazer shipped a governed natural-language BI agent plus an enterprise AI governance hub for a Fortune 500 CPG.

• 100% correct answers in the P&L pilot
• 4 systems integrated; Phase 2 approved

A high-volume support operation tested whether LLMs could safely automate first-line support.

• POC trained on 40,000+ real support tickets
• Validated by the CEO, CPO, and ML team, then grew into an embedded sprint

Enablement framed around existing consulting rigour, not novelty.

• ~300 staff across functions; 120 in hands-on in-person workshops
• Director Q&A built reusable Claude accelerators from messy inputs

Workflow-first training across the full reporting cycle, not AI theory.

• RTF/RISEN/RODES prompting for research, transcription and headlines
• NUJ-aligned guardrails kept AI inside editorial standards

Compliance treated as the unlock, not the blocker — Part 2 handled with PHI.

• De-identification layer strips PHI + 42 CFR Part 2 / SUD data
• Untouchable records became a sellable, monetizable data asset

Senior expertise turned into a self-serve asset instead of a standing interruption.

• Queryable knowledge brain lets juniors self-serve precedent
• Cut senior time ramping juniors ~60%

Scattered broker knowledge centralized before any outreach was retargeted.

• Auto-ingests every broker's email + text into one client brain
• Property-to-buyer matching lifted sales ~7%

Response speed made visible and enforceable before any sales process changed.

• Real-time tracking keeps every order under the 30-minute line
• Alerts before orders go cold recovered ~30% of leaking revenue

Site systems unified into one live source of truth before reporting was rebuilt.

• Cut monthly reporting from ~3 days to same-day (85% less)
• Query layer reclaimed 350+ analyst hours a year