BlueliftAI
Services and case studies

AI inside your operations, without replacing the core

AI projects we build inside our clients’ operations: from data and pilot to production, connected to the systems they already run.

Book a callSee case studies
Custom AI agentsFrom data and pilot to production, inside your infrastructure.
Training and adoptionPrograms that get teams working with AI every day.
Modernization without replacing the coreAI connects to the systems you already run.
By industry

What we automate and what we measure

Compliance, lending and customer service

AI for banks that modernize without replacing the core

We automate the most time-consuming processes in compliance, lending and customer service, connected to the systems the bank already has.

  • Smart KYC

    Customer onboarding with the file already reviewed and a single request for whatever is missing.

    What we measure: Onboarding time

  • AML Intelligence

    Every alert reaches the officer already investigated, with findings and a draft report.

    What we measure: Analysis time per alert

  • AI credit analyst

    Reads financial statements and loan file documents, citing the source of every data point.

    What we measure: Days to decision

Related case: KYC and AML Intelligence: corporate onboarding with the file reviewed by AI

How we work

  1. 01

    Discovery

    We map the process with the team that runs it.

  2. 02

    Baseline

    We measure the current process before writing any code.

  3. 03

    Build

    Weekly cycles with a demo to end users, in your infrastructure.

  4. 04

    Measured operation

    Results against the baseline and handover to your team.

Case studies

Projects inside our clients’ operations

Financial institution · Confidential

KYC and AML Intelligence: corporate onboarding with the file reviewed by AI

How BlueliftAI automates document checks when onboarding companies: AI reviews the file, extracts every data point with its source document and leaves the officer a summary to decide on.

  • Banking
  • Compliance
  • Document Intelligence
Read the case

The problem

Onboarding a legal entity means reviewing bylaws, minutes, powers of attorney, financial statements and sworn declarations. Much of the effort goes into back-and-forth with the client over missing or expired documents, and the officer manually reviews what a system could read.

What we built

  • Reading of every document in the file, with the source page for each data point
  • Validation against the regulatory checklist and internal policy
  • A single request to the client listing everything missing, instead of several
  • A summary for the compliance officer, who makes the approval
  • An audit trail of every step, deployed in the institution’s cloud, without replacing the core or the AML engine

What we measure

Onboarding time
Days from the first document to an active account
First request
% of files completed with a single request to the client
Analyst hours
Review time per file

Always against a baseline measured before we build.

Payments company · Confidential

Partner support: every request with an owner, a deadline and follow-up

An agent that classifies requests from banks and merchants, routes them to the right team and flags them before the deadline, so nothing goes unanswered.

  • Payments
  • Support
  • AI agents
Read the case

The problem

Requests from partner institutions pass through several teams before they are resolved. Without a single tracking view, nobody can see who owns each case, and the institution finds out late what happened.

What we built

  • Automatic classification of every request by type and urgency
  • Routing to the responsible team with the full history
  • Alerts before the committed deadline expires
  • Draft replies for the support team, who review and send them
  • A tracking dashboard for management

What we measure

Resolution time
Days from when a request comes in to the reply
On time
% of requests resolved within the committed deadline
Reassignments
Times a request changes teams

Always against a baseline measured before we build.

Insurance company · Confidential

Self-service portals for policyholders and new customers

Two portals that take the policyholder experience out of manual handling: one for existing customers and one for people who want to buy new coverage.

  • Insurance
  • Portals
  • Customer experience
Read the case

The problem

The experience for policyholders and prospects was fragmented and relied on manual handling: checking a policy, paying a premium or requesting new coverage all went through a person.

What we built

  • Existing-customer portal: policies, account statement, payments and new coverage
  • New-customer portal: application, issuance and document upload
  • Integration with the insurer’s systems
  • Designed so policyholders can handle routine requests on their own

What we measure

Self-service
% of requests resolved without the team stepping in
Issuance
Time from application to policy
Online payments
% of premiums paid through the portal

Always against a baseline measured before we build.

Client names are withheld under confidentiality agreements. Interfaces are illustrative.

More published case studies: AI for a specialty insurer · An agent working through our backlog

Let’s start with the process that hurts most

A 30-minute call with the team that owns the process: we tell you whether it can be automated and how we would measure it.

Book a callFree AI diagnostic