Explore Legacy Lifter Now
The Lifter
- The Lifter
Context Lives in Pieces
Teams pay for it with technical debt and reverse engineering tax
The Lifter is an agentic AI platform that reduces technical debt, accelerates modernization, and keeps business operations moving.
The Debt
40% of your IT balance sheet is technical debt.
The Blind Spot
System changes, and understanding doesn't keep up.
Engineering Context Keeps Getting Rebuilt?
Critical knowledge is scattered, and more effort is spent understanding it. Undocumented logic and testing gaps add friction to day-to-day engineering decisions.
Complex business logic is hidden in code.
58–70%
of a developer’s time goes into understanding it.
Meaning and rules get lost as data moves.
50%
of a data professional's week goes to work already done.
Test failures take too long to diagnose.
72%
of automated test failures are false positives.
Every incident starts with rebuilding the context.
At $2M
for every hour of a high-impact outage.
Capture the Context. Build On It.
The Lifter takes over repetitive work using agentic AI across code, data, releases, and tickets. What was learned stays available for the next change, reducing the need to reread, recheck, and restart. The longer it runs, the less effort it takes to do the same work.
Your Engineering Estate
The context alreasy exists as
The Lifter
Turns scattered information into useful knowledge
What it Enables
More momentum
One Platform, Four Purpose-Built Modules.
The Lifter brings specialized Agentic AI intelligence to four areas where engineering teams spend significant time and effort: legacy, data, testing, and application management.
 |
 |
 |
 |
|
|---|---|---|---|---|
 Best for |
Undocumented codebases and legacy applications | Complex data challenges at scale | Enterprise testing and complex releases | Application management and incident resolution |
 Outcome |
Understand your codebase in weeks with traceable system knowledge | Harness your data at a superhuman scale | Accelerated testing that holds up in production | Agentic AMS that carries context forward and resolves faster |
 Value Delivered |
15× faster analysis 40% lower engineering effort |
87–88% of drafted catalog entries accepted as-is | 75% reduction in test design effort 100% requirement traceability |
25–40% MTTR improvement $2M lost per outage hour |
 Next Step |
Start the Discovery | Engineer Data Smarter | Build Release Confidence | Diagnose Incidents |
-
How The Lifter Works?
01Application code02Read & analyze03Map dependencies04Extract rules & intent05Build traceable knowledge06Generate specificationsLegacy Lifter
What it Understands?
Codebases, dependencies, business rules, data flows, jobs, and application intent.
Reads
- Source code
- Application dependencies
- Data flows
- Embedded business rules
- Job relationships
- Documentation where available
What it does?
Reverse engineers the application, line by line.
- Maps dependencies and relationships
- Extracts business rules and logic
- Analyzes data flows
- Maps job dependencies
- Identifies redundant code
- Extracts documentation
- Interprets application intent
- Generates structured specifications
Output
A traceable knowledge base and modernization-ready specifications.
Built for
For engineering teams ready to change core systems without relying on tribal knowledge.
-
How The Lifter Works?
A visual showing the agent/capability flow.
01Data Sources02Discover03Ingest04Transform05Validate06Catalog & Define07ConsumeData Lifter
What it Understands?
The systems, code, definitions, dependencies, and rules that shape how your data works.
Reads
- Database schemas
- Stored procedures
- ETL code
- Documents
- Query history and logs
- Data transformations
- Business definitions and metric logic
What it does?
Reads your systems and drafts the work across the data lifecycle.
- Builds source inventories and dependency maps
- Assesses complexity and workloads
- Designs target schemas and storage
- Converts ETL and transformation logic
- Drafts quality rules and anomaly checks
- Creates catalog, lineage, and metadata entries
- Defines metrics and semantic models
- Supports data consumption through SQL, BI, and APIs
Output
Harness your data at a superhuman scale, with more work done and less manual effort.
Built for
For data teams tired of solving the same problem twice.
-
How The Lifter Works?
A visual showing the agent/capability flow.
01Requirements & code02Understand03Design tests04Generate & execute05Diagnose & self-heal06Learn & improveTest Lifter
What it Understands?
Requirements, code, workflows, tests, and execution signals.
Reads
- Business requirements
- Requirement changes
- Application code
- Existing test suites
- UI and application sessions
- Execution results
- Defect and production signals
What it does?
Designs, generates, runs, and improves tests.
- Structures requirements and user stories
- Identifies gaps and ambiguity
- Generates risk-based test cases and scripts
- Executes test suites
- Diagnoses failures
- Self-heals broken automation
- Feeds quality signals back into testing
Output
Evidence-backed coverage and release confidence.
Built for
For teams who want to walk into the release meeting with evidence, not a coverage number.
-
How The Lifter Works?
A visual showing the agent/capability flow.
01Application Estate02Build Living Context03Understand the Incident04Assess Business Impact05Recommend Remediation06Learn & Carry ForwardAMS Lifter
What it Understands?
Your application estate, incidents, dependencies, and operational history.
Reads
- Application and technical dependencies
- Incident and ticket history
- Runbooks and KEDB records
- Architecture and configurations
- Business context and process details
- Ownership and operational knowledge
What it does?
Builds a living context graph for every incident.
- Connects incidents to dependencies, changes, and prior fixes
- Diagnoses incidents using historical evidence
- Surfaces business impact and resolution options
- Keeps high-risk actions behind human approval
- Proposes approved resolution options within defined scope
- Carries findings and prior context to the next engineer
Output
A governed operational record that carries context forward.
Built for
For support teams tired of starting every escalation from scratch.
Skip The Repetitive Work That Keeps Coming Back
The Traditional Way
Manual archaeology
Trapped Tribal Knowledge
Context rebuilt repeatedly
Guesswork-driven decisions
Brittle automation
Cold escalations
The Lifter Way
AI-assisted system understanding
Traceable shared knowledge
Context carried forward
Evidence-backed decisions
Self-healing automation
Context-aware diagnosis
What The Lifter Changes
Legacy Lifter
Analyze 15× faster. Cut engineering effort by 40%.
Data Lifter
Improve semantic accuracy by 20 points, from 48% to 68%.
Test Lifter
Achieve 100% requirement traceability, from day one.
AMS Lifter
Cut MTTR by 25–40% within 12–18 months.
Designed With Your Priorities in Mind
Security at Every Layer
Engineered to protect enterprise environments with secure data access.
Built for Your Setup
We support on-premises, cloud, and hybrid deployment options.
Data Stays Yours
Your code and data stay within your environment where supported.
You Set the Rules
Decide what AI can recommend, prepare, or act on.
Experts Stay Involved
Our experts validate AI outputs where judgment matters.
Real Stories,
Real Impact
Put The Lifter
to the Test
Run a focused 4-week Proof of Value against your environment.
Frequently Asked Questions About The Lifter
1. What is The Lifter?
The Lifter is an agentic AI platform built to reduce technical debt, accelerate modernization, and keep business operations running. It uses specialized AI agents to understand complex enterprise systems, from undocumented legacy codebases to data platforms and production testing, while engineers review and approve the work.
2. How are the four modules from The Lifter, different?
Each module addresses a distinct part of the application lifecycle. Legacy Lifter tackles the reverse-engineering tax by recovering business logic and dependencies from undocumented codebases; Data Lifter applies agentic AI to data engineering; Test Lifter generates and maintains tests that hold up in production; and AMS Lifter uses a living knowledge base to help teams diagnose and resolve incidents with context.
3. Does The Lifter work with our existing systems and tools?
The Lifter is designed for complex enterprise environments and works across legacy applications, data platforms, testing environments, and application support workflows. Its agents work with the systems and engineering context already present in the environment, including code, requirements, data lineage, incidents, and operational knowledge.
4. Where does our data/code reside?
The Lifter supports on-premises, cloud, and private cloud/VPC deployment, giving enterprises options based on their environment and requirements. For organizations working with sensitive code and data, deployment within a controlled environment provides an important layer of governance.
5. How much human oversight is involved?
The platform is designed around human-in-the-loop governance. AI agents plan, execute, and validate work, while engineers review outputs and approve outcomes where engineering judgment matters; the platform also provides review, approval, and audit trails for agentic actions.
6. Can we deploy The Lifter on-premises?
Yes. On-premises deployment is supported, alongside cloud and private cloud/VPC options. This gives enterprise teams the flexibility to align The Lifter with their existing infrastructure and deployment requirements.
7. What happens after the Proof of Value?
The Proof of Value establishes the baseline, runs a focused workflow against your environment, and measures the resulting impact. From there, the evidence gives your team a basis for deciding whether to expand the use of The Lifter and where it can deliver the most value.