Agentic AI for Legacy Modernization

Your legacy,
finally
understood.

Agents do the work. Humans make the call. MIRA reads your legacy code, extracts the business rules with the line each came from, and lets your people decide. Modernize it, or keep it changing safely, on one platform.

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The pitch in ten seconds

We turn the code nobody fully understands into rules everybody can read, check and approve.

SEEWe read your code and write down what it does, in plain words, with the exact line each rule came from.
DECIDEAgents do the heavy lifting. Your people approve every rule that needs a judgment. Nothing is approved silently.
MOVEMaintain or modernize on one platform, from first look to production. Built to cut the time and the surprises.
01The experts are retiringHow the system works lives in a few people's heads.
02Days of readingA small change needs days of reading code before anyone dares to edit it.
03A lost first yearModernization projects spend year one finding out what the system does.
The market
$68BApplication modernization market, 2027 projection, about 16% annual growth
$52.5BAddressable application modernization market by 2030
$7.9BMainframe modernization market, 2025
$3TCommerce processed on IBM mainframes every day
500M+
Lines Transformed
50+
Enterprise Deployments
10+
Years of R&D
1
Platform for Modernization & AMS
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MIRA Demo Center — Interactive Workflows Get Access
MIRA in Action

See live modernization

From COBOL to Visual Basic — watch MIRA transform legacy systems through a live demo video and interactive workflow walkthroughs.

Live Demo Video
340k lines COBOL → Java Spring Boot in 72 hrs
COBOL Modernization
Interactive end-to-end workflow
COBOL + Re-Imagine
Modernization with re-architecture
Broadcom / CA Coolgen
COBOL modernization workflow
Oracle Forms
Forms modernization workflow
Visual Basic
VB modernization workflow
Open Demo Center ↗
The Status Quo

Why general-purpose
AI falls short

"I paste my COBOL into a chatbot. It gives me plausible Java. It's wrong in ways I won't discover until production."

Generic AI tools see code snippets. MIRA sees your 40-year interconnected ecosystem — every dependency, every undocumented business rule, every calling program.

No Context

They see snippets, not the 40-year interconnected ecosystem your business depends on.

Hallucinations

They invent dependencies, business rules, and transformation paths that don't exist.

No Memory

They forget what PROC-WIRE-001 does across 47 calling programs by the next prompt.

No Execution

They suggest process but cannot convert, test, or deploy a single line of real code.

What it is

One platform for the whole life of an application.

ScopeDefine what is in, and what done means
DiscoverRead source, extract rules, score risk
DesignServices, data, waves, roadmap
TransformCode and tests from the rules
ValidateQuality, security, test evidence
DeployBuild and ship to target
UATBusiness users test it
MonitorWatch it in production
Every stage reads from and writes to one context store. Nothing is retyped. Nothing is lost between stages.
The engine underneath

A memory for your code, and a map of how it connects.

The context store holds everything we learn about your systems: programs, screens, data, and every business rule in plain words with its source line.

The semantic knowledge graph links all of it. It knows which screen shows which result, which program reads which data, and which rule guards which decision.

Go deeper: how it works
Why it is different

Five things to remember.

1Grammar-basedSource is parsed like a compiler reads it. Same input, same output.
2Agents liftThey sort, classify and draft. They never supply new facts.
3Humans decideEvery rule that needs judgment goes to a person. Nothing is approved silently.
4EvidenceEvery rule, call and link points to a file and line.
5Checked answersAnswers are checked against the store. If it is not there, the answer is replaced.
Two jobs, one engine

Every application needs both. Most teams struggle with both.

ModernizeClear the tech debt

Move off the old stack without losing what the system knows.

  • 1Read everything. The whole estate: source, jobs, screens, data.
  • 2Extract the rules. Each with its source lines. People review the judgment calls.
  • 3Design the target. Services, data, migration waves, roadmap.
  • 4Generate code and tests from the same rules.
  • 5Validate, deploy, accept. Quality and security scans, then business users test.
Maintain · AMSNewKeep it changing, safely

Fixes, features and upgrades, every week, without breaking what works.

  • 1Scope the cycle. Pick the programs and areas in this cycle.
  • 2Read the backlog. Each ticket is matched to candidate code. A person confirms.
  • 3See the impact before editing.
  • 4Make the change and compare the rules before and after.
  • 5Get the tests for the rules the change reaches.
One context store sits under both. What we learn while modernizing is what makes maintenance fast. Both are the same software lifecycle: one removes the debt, the other keeps the application alive.
Built for the systems that matter

Where the code carries money, patients and benefits.

Banks, insurers, payment processors, health networks and public agencies run on systems that cannot afford a wrong answer.

Banking
Insurance
Payments
Healthcare
Government
Languages and platforms
Mainframe, mid-range and AS400
COBOL + JCLUnisysRPGNatural + AdabasCA Telon
Enterprise, integration and desktop
JavaOracle Forms + PL/SQLUnifaceVisual Basic 6 + Excel VBAIBM App Connect Enterprise (formerly IIB)

More are added over time.

For Partners and Integrators

Start where customers
already spend.

Customers know application maintenance. They already buy it, on a service and a rate card. Modernization is a big budget ask. AMS with MIRA is the way in, and modernization grows from it.

Step one: the AMS loop, run on MIRA New
  • 1Scope the cycle. Pick the programs, jobs or business areas in this cycle. We map what they touch.
  • 2Read the backlog. Each ticket is matched to candidate code. A person confirms before anything is edited.
  • 3See the impact. The programs, data, jobs and rules a change can reach, with evidence.
  • 4Make the change in the legacy code, knowing what else is affected.
  • 5Check what changed. Rules are compared to the baseline. An unintended change is flagged.
  • 6Get the tests for the affected rules, built from each rule's own boundaries.
Same ticket, two ways

Without MIRA

  • Days reading code to find what a change touches
  • Impact guessed from memory
  • Regression tests for everything, or for nothing
  • Knowledge walks out with the people

With MIRA

  • Each ticket is matched to candidate code and a person confirms it
  • The programs, data, jobs and rules a change reaches, with evidence
  • Tests chosen for the rules the change reaches
  • The knowledge stays in the store
What the same rate card now delivers
FasterImpact analysis in minutes, not days of reading code.
More accurateEvery change is checked against the baseline rules before release.
Fewer hoursTests chosen for the rules a change reaches. Less rework.
More productiveSmaller teams look after more applications. Knowledge stays when people leave.
Better marginA lower cost to serve and a more predictable margin for the integrator.
Step two: grow into modernization

Modernization is AMS taken further.

1AMS with MIRAThe same service and rate card, delivered faster and with more accuracy. Smaller teams look after more applications, and the integrator keeps a more predictable margin.
2The store gets richerEvery cycle adds rules, links and tests. The application stops being a black box.
3Modernize in slicesOne application and one wave at a time, from facts already held. A new stack and a new business, in steps a budget can carry.

Same engine. Same context store. A bigger outcome, reached in steps a budget can carry.

For the integrator

  • Lower cost to serve in AMS
  • A more predictable margin
  • A path to modernization revenue inside accounts you already run
  • Your own brand, if you wish

For the customer

  • Lower AMS spend
  • Fewer production surprises
  • The knowledge of the system kept, not lost
  • A practical way to modernize without one big ask
How We Compare

Five ways to solve this.
Where each one stops.

Our biggest difference

Facts we parse, not facts a model guesses.

DeterministicSource code is parsed with the grammar of its language. The same input gives the same output every time. Facts do not come from a model, so they are not made up.
Self-correctingAgents and people check each other. A person's correction is fed back, so the platform learns and gets sharper with use.
End to endOne platform from scope to production monitoring. Nothing is retyped between tools. Nothing is lost between teams.
Do it by hand
Where it stops

Your own people know the business. But it is slow, costly and depends on experts who are retiring. Understanding the system eats the first year.

Where we differ

We read every program, every time, and keep what we learn.

General-purpose AI and AI-native tools
Where it stops

Quick to start and good at summaries. But models have seen little mainframe code, read a sample rather than the whole estate, and can vary from run to run.

Where we differ

We parse the whole estate first. Agents add no facts of their own.

Integrators on their own
Where it stops

Large teams and deep client relationships. But cost grows with headcount and each engagement starts again from reading code.

Where we differ

We make integrators faster, under their own brand if they wish.

AI coding agents
Where it stops

Strong at writing and fixing modern code. But old systems lack the business context they need, and they can answer confidently when they should flag doubt.

Where we differ

Every fact has a source line. Every judgment call goes to a person.

Other graphs and context tools
Where it stops

Good at mapping structure. But built for modern code first, they draw the map without knowing what old code means for the business.

Where we differ

We have 10+ years of legacy experience, and the map feeds code, tests, deployment and monitoring.

Deterministic. Self-correcting. End to end.
  • Every fact traced to a line of code
  • Same answer every run
  • People approve every judgment call
  • Scope to monitoring in one place
The others read code. We understand it, prove it, and keep it current.
Go deeper

The context store and the knowledge graph, in plain English.

Most people have never heard of either. Read this section once and you can explain them to anyone.

Idea 1

The context store

What we know. Think of a filing cabinet for one application. Every drawer is labeled. Every page carries the page number of the original book. It is a store of facts, not a pile of documents.

Idea 2

The semantic knowledge graph

How it connects. Think of a subway map. The stops are programs, screens, data and rules. The lines between them are labeled: calls, reads, writes, guards. You can see what is connected to what.

Inside the store

What it holds, for every project

Programs, jobs, screens, dataEvery one of them, listed and described.
Business rulesThe condition, the action, a plain-words description, and the source lines.
Calls and data accessWhich program calls which, and the data each one runs against.
Purposes and summariesA plain-language purpose for each program.
Links between all of itSo nothing sits on its own.
What it does not holdIt says which parts were read and which were not. It never pretends.
Inside the graph

How a question travels

ScreenProgramBusiness rule Data tableBatch job shows onappliesreadscallswrites
Real questions it answers:
  • What is affected if this field changes?
  • Walk me through everything the interest calculation touches.
  • Which screens show the result of this rule?
The answer comes from following named links, with the source line as evidence. It does not come from finding text that looks similar.
What this makes possible
Impact in minutesStart from a field, cross the program, end at the data and rules.
Domain walk-throughsFollow a business area from the batch job to the rules, in order.
Code from structureThe generator reads steps, branches and rules directly from the map.
One vocabularyBusiness words and code names are linked. Ask in business language.
Tests that know whyEach test is tied to a rule, and marked out of date when it changes.
Why you can trust it
EvidenceEvery fact points to a file and line.
FreshWhen source or rules change, affected items refresh. Anything out of date is shown.
IsolatedEvery read is limited by tenant, project and user. Sensitive material stays out of shared text.
CheckedAnswers are verified against the store. If it is not there, the answer is replaced.
Where your code goes

Your estate stays yours.

Isolated workspaceEach customer gets its own workspace. Every read is scoped by tenant, project and user.
Runs where you need itThe platform can run in your own environment.
Sensitive stays outProjects and rules marked sensitive are kept out of shared text.
People stay in controlRules that need judgment, and disagreements between sources, always go to a person.
How to start

Start small. Grow when you are ready.

1Discovery on one applicationSee what the platform finds in your own code. No commitment to modernize.
2Maintain one cycleRun a maintenance cycle on MIRA. See the impact, the rule changes and the tests.
3Modernize a waveMove one application, one wave at a time, from facts already held.
Questions we hear
Does AI write my code?

Agents help generate code, but they work from facts extracted by parsing your source. Every rule they use has a source line. People review the rules that need judgment, and tests check the result.

What stops it from making things up?

Facts do not come from a model. They come from the parse of your code and carry their evidence. When the assistant answers a question, the platform checks the answer against what the store returned and replaces it if it names something the store did not hold.

Where does my code and data go?

Each customer has an isolated workspace. The platform can run in your own environment. Projects and rules marked sensitive are kept out of shared text.

Can we start small?

Yes. Many teams begin with discovery on one application to see what the platform finds, then move to maintenance or modernization.

Do we have to modernize to benefit?

No. Understanding and maintenance run on the legacy code as it is. Modernization is an option, not a requirement.

Built for Every Stakeholder

Made for the people
who matter most

De-risk your modernization. Understand first, then change.

Get the full intelligence picture before a single line of code changes — risk profiles, complexity scores, transformation plans — so you commit to timelines with confidence.

70%
Reduction in project timeline
100%
Business rule parity guaranteed
SOC 2
Designed and mapped to SOC 2 criteria
$0
External data exposure — ever
MIRA Discovery Report
// Wire Transfer — Executive Summary
 
programs: 127 interconnected
lines_of_code: 340,847
external_interfaces: 23
undocumented_rules: 47 extracted
risk_score: "HIGH" → mitigation ready
 
target: "Java Spring Boot + K8s"
scope: "defined per application"
status: "Ready to transform" ✓

A senior teammate who actually knows the codebase.

Ask MIRA anything. She responds from parsed metadata — not internet patterns. What does PROC-WIRE-XFER-001 call? She knows. What undocumented rules are in FEE-CALC-007? She extracted them.

847
Unit tests auto-generated
94.2%
Code coverage achieved
0
SonarQube blockers
72h
Full module conversion
Ask MIRA — Business Rules
// "What rules are in FEE-CALC-007?"
 
FEE-CALC-007 — 7 rules extracted
 
Rule 1: Domestic <$10K → flat $15 (ln 234)
Rule 2: $10K–$100K → 0.15%
Rule 3: >$100K → 0.10% (cap $500)
Rule 4: Intl SWIFT → $45 + 0.20%
Rule 6: VIP tier3+ → 50% discount
 
confidence: 99.8% | source: parsed AST

Your infra, your model, your rules. Zero exposure.

MIRA runs inside a secure, isolated container within your infrastructure. No source code transmitted externally. No proprietary logic used for training. Air-gapped deployment available.

Air-Gap
No internet required option
BYOM
Bring your own model
SOC 2
Designed and mapped to SOC 2 criteria
K8s
Native Kubernetes deployment
Security Architecture
// MIRA Deployment — Security Profile
 
deployment_mode: "isolated_container"
external_api_calls: 0
source_code_transmitted: false
training_data_used: false
 
model_provider: "bring_your_own"
audit_trail: full_immutable_log
compliance: ["SOC2", "ISO27001"]
Transparent Pricing

Built for enterprise scale.
Priced to match your project.

Tier-based subscription plus usage — Free, Starter, Pro, and Scale — sized by your estate, not your headcount. Use the interactive calculator to estimate your project cost.

View Pricing & Calculator →
Investor Relations

A massive market.
A defensible moat.

The global legacy modernization market is accelerating. Ionate has spent 10+ years building the IP, tooling, and enterprise relationships that cannot be replicated quickly.

$68B
Global legacy modernization market by 2027 (CAGR 16.4%)
$3.8T
Global tech debt estimated by McKinsey — growing annually
95%
Of Fortune 500 still run COBOL-based core systems
Request Investor Deck
01 / MOAT

10+ Years of Proprietary Knowledge Graphs

MIRA is built on structured metadata from 50+ enterprise deployments and 500M+ lines of code. This institutional knowledge cannot be replicated by a prompt engineer with a general-purpose chatbot.

02 / TRACTION

Enterprise Customers Across Banking, Insurance & Government

Customers include major financial institutions handling billions in daily transactions. Long-cycle, high-ACV, high-retention relationships — not one-off projects.

03 / MODEL

Recurring License + Consumption Revenue

The subscription-plus-usage model creates predictable base revenue with strong consumption upside. Minimum 5-user, 12-month contracts deliver high LTV from day one.

04 / TIMING

Agentic AI Unlocks a New Growth Horizon

MIRA transforms proven tooling into an always-on AI agent that dramatically expands TAM and compresses sales cycles across the enterprise market.

Enterprise Security

Your code never
leaves your
environment.

MIRA runs in a secure, isolated container within your infrastructure. No source code is sent to external APIs. No training on your proprietary logic. Ever.

Talk Security
🔒
Air-Gapped

No internet required

✓
SOC 2

Designed and mapped to SOC 2 criteria

🧠
BYOM

Your model, your rules

📋
Audit Trail

Full immutable logs

🛡
Zero Trust

Network policy

🌐
Multi-Cloud

AWS, Azure, GCP

Legacy understood.

Transformation
unlocked.

Point MIRA at your codebase and get a complete ecosystem map in 48–72 hours. No commitment required for discovery.

Request a Demo sales@mirastudio.ai
COBOL to Java Spring Boot Natural/Adabas Modernization Oracle Forms & Reports JCL to Spring Batch VSAM to DB2 / Cloud DB CICS to REST APIs COBOL to Java Spring Boot Natural/Adabas Modernization Oracle Forms & Reports JCL to Spring Batch VSAM to DB2 / Cloud DB CICS to REST APIs
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