GoFactAI
AI Workflow Automation

Automate
the work that matters.

Fact AI Lab deploys production-grade AI that extracts, routes, and processes high-value workflows — 80% faster, with error rates under 0.5%. Built for SaaS, real estate, and financial services. ROI in 30 days, not 6 months.

SaaSCustomer success, contract review, usage analytics
Real EstateLease abstraction, property data, tenant screening
FinanceDocument processing, reporting, underwriting assist
Book a 20-Minute Discovery CallHow We Handle Your Data

No commitment required. 30-day automation pilot available.

Built for teams inFinancial ServicesLegalInsuranceHealthcareAsset Management

The automation gap is costing you

Your team spends 10+ hours a week processing documents and routing tasks that AI can handle. The tools exist. The integrations do too. What's missing is a production-grade system that doesn't hallucinate.

80%
faster document processing

Companies automating document-heavy workflows — lease abstraction, loan underwriting, contract review — cut processing time from hours to minutes with AI extraction.

0.5%
error rate at production

Eval-first deployment means AI outputs are scored against your ground truth before they reach your team. Typical manual processing runs 5–10% error rates.

30 days
to measurable ROI

Most AI pilots take 6 months and produce a demo. We instrument one real workflow, measure the impact, and deliver production automation — in one month.

How we build automation that sticks

Not a chatbot layer. Not a prompt wrapper. Production automation infrastructure — with verification built in so your team can trust what ships.

Document Intelligence

AI that reads your documents — leases, loan applications, contracts, statements — and extracts structured data at scale. From unstructured to decision-ready in minutes, not hours.

80% processing time reduction

Workflow Automation

Orchestrate multi-step processes: intake, triage, routing, approval, exception handling. Reduce manual handoffs, catch errors before they compound, and give your team time back for high-value work.

0.5–1.5 FTE labor saved per workflow

Eval-First Quality

Every AI output is scored against your ground truth before it reaches your team. Error rate under 0.5% in production — with built-in privacy, audit logging, and compliance guardrails your legal and IT teams can sign off on.

< 0.5% error rate at production

Up and running in a day, not a quarter

Integration is designed for engineering teams that are already moving fast. Fact AI Lab wraps your existing stack, not the other way around.

01

Connect

Point Fact AI Lab at your existing LLM endpoints — OpenAI, Azure OpenAI, Amazon Bedrock, or self-hosted. No model changes. No prompt rewrites. Setup takes under 2 hours.

SDK in Python and TypeScript. REST API fallback.

02

Instrument

Our verification layer intercepts outputs in real time, scores them against your source documents, and appends a cryptographically signed verification record. Average latency overhead: 180ms.

180ms median latency addition in production.

03

Audit

Every interaction is logged with full provenance: prompt, retrieved context, model version, output, verification score. Export to PDF or structured JSON on demand for any regulator.

SEC, FINRA, FCA, OSFI report templates included.

30-Day Automation Pilot

Ship one automation in 30 days

We identify your highest-ROI workflow, build the automation, measure the impact — and hand it over running. No six-month sales cycle. No PoC graveyard. If it doesn't reduce labor hours in 30 days, you owe nothing.

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Pilot Deliverables

  • One production automation — live and processing real documents
  • Baseline error rate measurement (before and after)
  • Labor hours reclaimed — tracked over 30 days
  • Data privacy and integration review for your stack
  • Roadmap for 2–3 additional automation opportunities

What Clients and Collaborators Say

LinkedIn recommendations alongside anonymized project outcomes from client engagements.

LinkedIn recommendation from Wes Regan, PhD Candidate at UBC SCARP
LinkedIn recommendation from Keyi Tang, Staff Applied Scientist at DoorDash
LinkedIn recommendation from Alexey Iskrov, Engineering Leader
LinkedIn recommendation from Amir Ghaffari, CFO

AI extraction pipeline reduced loan document review from 3 days to 4 hours.

VP Operations · BC Credit Union

RAG system resolved 70% of tier-1 support tickets without escalation. ROI positive in month two.

CTO · Series A SaaS

AI audit framework surfaced compliance gaps missed by the internal team across 3 review cycles.

Chief Risk Officer · Insurance Firm

Our methodology

The SAFE Framework

How we approach every AI deployment — from first conversation to production monitoring.

SScope

Define which workflows need AI and which don't. Not every process benefits from automation — the ones that do need a clear brief before a line of code is written.

AAudit

Instrument every AI output with verification scores, source grounding, and immutable logs. Every decision becomes traceable before it reaches a user or examiner.

FFit

Match the right approach to each workflow — LLM, RAG, agents, or classical ML. The model that fits earns its place. The one that doesn't gets ruled out early.

EEval

Evaluation-first deployment. Measure hallucination rate, latency, and accuracy before shipping. Monitor the same metrics after launch. Ship when the numbers earn it.

Every Fact AI Lab engagement follows this framework.

Pedram Agand, Founder of Fact AI Lab
Pedram Agand
Founder, Fact AI Lab — SFU & AI Research Background
·AI systems researcher with focus on reliability and verification
·Published work at IROS, NeurIPS workshops
·Built and deployed LLM systems in regulated contexts
·Direct background in compliance-adjacent AI applications
Research profile →
Why Fact AI Lab

Built by someone who has sat in your compliance team's chair

I didn't build Fact AI Lab because AI is trending. I built it after watching compliance teams at financial firms reject valid LLM use cases because they couldn't explain the outputs to examiners.

The technology to verify AI outputs exists. The infrastructure to make that verification audit-ready — that's what Fact AI Lab provides. Your AI investment should not be a liability. It should be defensible.

Talk to the Founder

Common questions

Free Guide

16 AI workflow with proven ROI for modern Operators

Sixteen production-tested automations — each with the failure mode it prevents and the metric that proves it works.

Tech & SaaS (5 workflows)Financial Services (5 workflows)Cross-Vertical Infrastructure (3 workflows)Legal & Operations (2 workflows)Healthcare (1 workflow)
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Ready to make your AI defensible?

20 minutes. No slides. We talk about your specific workflows, your regulatory environment, and whether Fact AI Lab is the right fit.

Responding to all inquiries within 24 hours.

Program PartnersMicrosoft for StartupsAWS for StartupsChang School at SFUL2M Accelerator