Now booking Q3 2026 · post-raise delivery slots

Ship what you raised for
in clinical ops, claims and billing, privilege review, policy servicing, freight dispatch, the close cycle, RFI triage, or customer journeys
in weeks.

FineCore.dev is the production engineering squad for domain-first founders at Seed and Series A. We ship AI into the workflows you already run: claims, charts, contracts, freight, billing. Stable, auditable, and held to a number you set. No CTO required.

/ Use cases

If your team runs it, we can ship AI into it.

Every build runs on the same system, Acceptance-Led Delivery: retrieval grounded in your documents, agents gated by human approval, evals before anything rolls out. Pick your vertical to see it in your workflow.

Built inside HIPAA from the first commit.

PHI boundaries, EHR-adjacent data, clinician review on every output. This is the constraint set we know best: every delivered build on this site is clinician-facing.

  • Clinical documentation copilotdoc time −35%
  • Prior-auth & claims triagehandle time −40%
  • Point-of-care decision support>94% citation accuracy
  • Drug-safety lookup over FDA labels100% on-prem inference
  • Medical coding & denial appealsICD-10/CPT, coder-reviewed
RAGEval harnessHIPAA baselineClinician-in-the-loop
Interactive tour · delivered buildsTour AleemIQ, CANN-DiS, and ElderGuard in motion
In production today: AleemIQ, CANN-DiS, ElderGuard.Case studies →

Citation-grounded output your counsel can defend.

RAG over matter files, transcripts, and prior work product. Every output requires attorney approval; immutable audit trail for malpractice review.

  • Privilege review & log drafting>92% citation match
  • Deposition prep, page-line cited11 wk to pilot
  • Contract triage & clause extractionplaybook deviations flagged
  • E-discovery & document reviewreviewer hours −70%
RAGAudit trailAttorney-in-the-loopEval set
Interactive demo · simulated dataWatch a privilege review run end to end
Reference scope: Series A legal AI for an ex–Big Law partner, no engineering bench.

Claims decisions with an adjuster's name on them.

FNOL intake, policy files, and adjuster notes are documents; decisions are rules plus judgment. We automate the documents and the rules, and route the judgment.

  • FNOL intake & claims triageadjuster-approved payouts
  • Policy issuance & endorsementsstraight-through, exceptions flagged
  • Underwriting intake & risk summariescited risk files
  • Fraud flags for SIU reviewevidence attached
Doc extractionRules + RAGAdjuster-in-the-loopAudit log
Interactive demo · simulated dataWatch a claim go from FNOL to adjuster sign-off
Insurers outsource $50B+ of claims and policy admin every year. This pattern brings it in-house.

Every dispatch plan clears your ops lead first.

Ingests load tenders, customs holds, and driver HOS; proposes routings and check-call scripts before anything writes back to the TMS.

  • Dispatch scheduling co-pilotempty miles −22%
  • Load tender → TMS write-backapproval-gated
  • HOS- & customs-aware routing9 wk pilot
  • Freight audit & paymentinvoice-to-contract match
TMS APILLM agentsApproval gatesEval set
Interactive demo · simulated dataWatch a dispatch plan clear ops review
Reference scope: post-Seed cross-border freight broker, US–Mexico lanes.

Close the books with an audit trail, not a chat window.

Agentic finance-ops workflows grounded in the ERP: tie-outs, variance explanations, journal entries, AP matching. Your controller approves each entry, and the log holds up in audit.

  • Close-cycle reconciliation copilot12 wk to production
  • Variance explanations from the ERPSOX audit-ready
  • Journal-entry draftingcontroller-approved
  • AP capture → GL coding → approval3-way match, exception-only
NetSuiteLLM agentsOPA policiesAudit log
Interactive demo · simulated dataWatch month-end close reconcile, entry by entry
Reference scope: close-cycle copilot integrated into client-side NetSuite.

Answers cited to the drawing set, routed to the right lead.

RAG over project documents, specs, and prior RFIs. Incoming questions land with the correct discipline lead, draft response attached.

  • RFI deflection & response drafting~30% deflection
  • Submittal triage to discipline leads10 wk to pilot
  • Spec & drawing-set Q&Acited to sheet refs
Procore APIRAGVector DBEval set
Interactive demo · simulated dataWatch an RFI answered straight from the drawing set
Reference scope: RFI deflection for a general contractor's project office.

Personalization on the systems you already pay for.

Natural-language product discovery and next-best-offer on a unified customer profile, deployed customer-side with acceptance tied to lift.

  • NL discovery & next-best-offer3× CTR lift
  • CRM personalization, Salesforce + CDP14 wk pilot → scale
  • Support deflection with cited answersCSAT-gated
  • Order, returns & billing inquiriesresolution-rate gated
SalesforceCDPVector searchRAG
Interactive demo · simulated dataWatch discovery, offers, and support run on one profile
Reference scope: national footwear retailer, customer-side deployment.

Targets shown are acceptance metrics: agreed before kickoff, measured before invoice.

/ Delivered

Shipped, in production, in regulated workflows.

A selection of delivered builds. Acceptance-led, customer-side deployments. NDA-bound engagements are not shown.

3
Builds in production
16 wk
Longest end-to-end build
1
Acceptance metric per engagement
0
Junior engineers staffed
Anesthesia · iOS 01 / Delivered

AleemIQ — HIPAA-compliant anesthesia decision support

An iOS app for ambulatory anesthesia providers. Anonymous case documentation + a RAG-grounded AI engine surfaces precedent from prior cases at point-of-care. Built for App Store submission.

16 wk
End-to-end delivery
HIPAA
Compliance baseline
FlutterLaravelMySQLFrontier LLM / Llama 3RAGRLHF
Pharmacology · on-prem 02 / Delivered

CANN-DiS — Cannabinoid drug-interaction chatbot

A clinician-facing chatbot for cannabinoid drug interactions. Local Gemma 2 inference with optional RAG over FDA DailyMed labels, FAISS retrieval, and Whisper voice input. Answers are grounded in cited drug labels.

100%
On-prem inference
FDA
DailyMed-cited sources
Next.jsFastAPIGemma 2FAISSWhisperRedis
Elder care · hardware 03 / Delivered

ElderGuard — privacy-first elder monitoring

Cross-platform app (iOS / Android / HarmonyOS) paired with WiFi-CSI sensing hardware: contactless fall detection, vitals (6–30 BPM respiration, 40–120 BPM heart rate), sleep analysis. No cameras, no wearables, signals never leave the home network.

3
Mobile platforms
6 mo
Free maintenance
React NativeRustESP32-S3WASMWebSocketFCM
Interactive tourSee all three builds in motion, recreated with synthetic data
/ Pricing

Productized pricing. Outcome‑bound. No hidden ramp.

Every quote reserves 15–20% for compute and tooling, so the price you see is the price that lands a measured outcome.

Foundation

$50K4–6 wk

One feature, shipped. A focused AI capability inside your existing app.

  • One AI-enabled feature
  • Eval set + observability
  • Production rollout
  • Runbook handoff
Book a call
First production feature after the round

Full-stack

$150–200K12–16 wk

Program-level rollout across multiple systems and departments.

  • Multi-system rollout
  • Customer-side deployment
  • Compliance artifact pack
  • Quarterly capability releases
Book a call
Multi-workflow rollout + compliance pack

Operate

$3–10Kper month

Post-launch monitoring, drift tuning, and ongoing optimization.

  • Eval drift detection
  • Prompt & retrieval tuning
  • Model & cost optimization
  • Monthly KPI report
Book a call
Post-launch; no internal ML team required

    / FAQ

    What founders ask before booking.

    That constraint shaped how we work. Every engagement opens by defining one acceptance metric in your language: documentation time, RFI deflection, empty miles. You watch it move in a Friday demo each week. The eval set that proves it is yours, so you can rerun it anytime or hand it to your future CTO as a day-one spec.
    You do. Code, eval sets, prompts, and infrastructure live in your repos and your cloud from day one. When the engagement ends, nothing leaves with us.
    Yes, and it's the default posture: customer-side deployment, audit logs at every layer, BAAs where required. When data can't leave the building at all, we run inference fully on premises. CANN-DiS above shipped that way.
    Hire them after the pilot. Two senior AI engineers run roughly $500K a year loaded and spend their first quarter ramping. A Foundation engagement lands a production feature for $50K in 4–6 weeks, and the runbook and evals we hand off make your first hire productive on day one instead of month four.
    We tune until acceptance, or we tell you in writing why the workflow isn't ready before you spend more. We never scope a multi-system rollout until a closed-loop pilot has hit its metric. And because models drift after launch, the Operate tier keeps the number honest month over month.
    / Who you'll work with

    No account managers. The call goes to the people who ship.

    New York–led, globally staffed. Every engagement is run by senior engineers who have shipped production AI before. Nobody fronts a junior bench.

    1. Kickoff call
      Elias
    2. Acceptance metric
      Elias + you
    3. Friday demos
      Build squad, weekly
    4. Architecture review
      Stan, kickoff → acceptance
    5. Handoff
      Runbook + evals, yours

    Elias Ali

    Founder & CEO

    Your first call and your single point of accountability, hands-on from discovery through rollout. Built FineCore around productized AI delivery.

    Stan Gu

    Advisor · ex-Google · ex-Reka

    Led teams behind Google's high-performance display ads services, then post-training and enterprise partnerships at Reka, shipping on-prem multimodal and agentic AI. Reviews every engagement's architecture from kickoff through pilot acceptance.

    Book a call.

    Tell us what you raised to build, the metric that proves it, and your target date. We respond in two business days with a scoped proposal.

    Pick a time

    Google Calendar works best full screen on a phone. Tap below to open scheduling in your browser. Same slots as desktop.