Back

Back

novolingo, Estate intelligence.

Uncover the knowledge inside your legacy estate.

novolingo is used within Mitra delivery to uncover hidden business logic, dependencies and knowledge from complex and legacy systems. It helps organise that understanding into reusable evidence for modernisation, impact analysis, engineering and operational decisions.

Request Demo

Request Demo

uncover
Showreel background
Play Video
insights

Integrated AI advice, engineering and operations

Core capabilities

Senior technology judgement stays close to the engineers doing the work. We help weigh priorities, sequence change and resolve trade-offs, then carry what we learn into delivering change and evolving operations.

Continuous Estate Mapping

Maps architecture, dependencies, transaction flows and embedded business logic across complex enterprise systems, and keeps the map current as they change.

Outcome: Prevents newly modernised estates from becoming opaque again.

Natural Language System Querying

Ask questions about your estate in plain English and receive grounded, traceable answers linked to underlying code and documentation.

Outcome: Accelerates decision-making without relying on specialist knowledge.

Modernisation & Upgrade Tooling

Version comparison, upgrade planning, API enablement and refactoring support, all sequenced against the live dependency map.

Outcome: Lower-risk change programmes with clearer delivery roadmaps.

Business Logic Extraction

Extracts undocumented operational logic directly from the codebase and writes it into a continuously maintained record.

Outcome: Critical knowledge remains accessible regardless of personnel changes.

Governance & Knowledge Validation

Subject matter experts validate, enrich and govern AI-generated intelligence through versioned and auditable workflows.

Outcome: A single validated record, ready as evidence for audit and change.

Developer Enablement & Onboarding

Guided learning paths, onboarding intelligence and visual knowledge maps accelerate understanding of complex systems.

Outcome: Faster onboarding and less reliance on what a few key engineers know.

Knowledge Risk & Dependency Analysis

Identifies institutional dependency risk, key-person exposure and undocumented operational ownership across critical systems.

Outcome: Reduced risk that a single departure strands a critical system.

Operational & Incident Correlation

Connects architecture intelligence with incidents, support workflows and operational signals across the estate.

Outcome: Faster root cause analysis and reduced incident resolution times.

Test Intelligence & Quality Assurance

Generates functional and regression test scenarios directly from legacy code and business rules.

Outcome: Safer releases and reduced risk during upgrades and transformation.

Continuous Estate Mapping

Maps architecture, dependencies, transaction flows and embedded business logic across complex enterprise systems, and keeps the map current as they change.

Outcome: Prevents newly modernised estates from becoming opaque again.

Business Logic Extraction

Extracts undocumented operational logic directly from the codebase and writes it into a continuously maintained record.

Outcome: Critical knowledge remains accessible regardless of personnel changes.

Knowledge Risk & Dependency Analysis

Identifies institutional dependency risk, key-person exposure and undocumented operational ownership across critical systems.

Outcome: Reduced risk that a single departure strands a critical system.

Natural Language System Querying

Ask questions about your estate in plain English and receive grounded, traceable answers linked to underlying code and documentation.

Outcome: Accelerates decision-making without relying on specialist knowledge.

Governance & Knowledge Validation

Subject matter experts validate, enrich and govern AI-generated intelligence through versioned and auditable workflows.

Outcome: A single validated record, ready as evidence for audit and change.

Operational & Incident Correlation

Connects architecture intelligence with incidents, support workflows and operational signals across the estate.

Outcome: Faster root cause analysis and reduced incident resolution times.

Modernisation & Upgrade Tooling

Version comparison, upgrade planning, API enablement and refactoring support, all sequenced against the live dependency map.

Outcome: Lower-risk change programmes with clearer delivery roadmaps.

Developer Enablement & Onboarding

Guided learning paths, onboarding intelligence and visual knowledge maps accelerate understanding of complex systems.

Outcome: Faster onboarding and less reliance on what a few key engineers know.

Test Intelligence & Quality Assurance

Generates functional and regression test scenarios directly from legacy code and business rules.

Outcome: Safer releases and reduced risk during upgrades and transformation.

Continuous Estate Mapping

Maps architecture, dependencies, transaction flows and embedded business logic across complex enterprise systems, and keeps the map current as they change.

Outcome: Prevents newly modernised estates from becoming opaque again.

Business Logic Extraction

Extracts undocumented operational logic directly from the codebase and writes it into a continuously maintained record.

Outcome: Critical knowledge remains accessible regardless of personnel changes.

Knowledge Risk & Dependency Analysis

Identifies institutional dependency risk, key-person exposure and undocumented operational ownership across critical systems.

Outcome: Reduced risk that a single departure strands a critical system.

Natural Language System Querying

Ask questions about your estate in plain English and receive grounded, traceable answers linked to underlying code and documentation.

Outcome: Accelerates decision-making without relying on specialist knowledge.

Governance & Knowledge Validation

Subject matter experts validate, enrich and govern AI-generated intelligence through versioned and auditable workflows.

Outcome: A single validated record, ready as evidence for audit and change.

Operational & Incident Correlation

Connects architecture intelligence with incidents, support workflows and operational signals across the estate.

Outcome: Faster root cause analysis and reduced incident resolution times.

Modernisation & Upgrade Tooling

Version comparison, upgrade planning, API enablement and refactoring support, all sequenced against the live dependency map.

Outcome: Lower-risk change programmes with clearer delivery roadmaps.

Developer Enablement & Onboarding

Guided learning paths, onboarding intelligence and visual knowledge maps accelerate understanding of complex systems.

Outcome: Faster onboarding and less reliance on what a few key engineers know.

Test Intelligence & Quality Assurance

Generates functional and regression test scenarios directly from legacy code and business rules.

Outcome: Safer releases and reduced risk during upgrades and transformation.

Request Demo

Request Demo

Logic Reasoning Explained

21

22

23

24

25

26

27

28

29

30

31

32

33

34

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

INCLUDE INCLUDES EQU.TERMWORK

INCLUDE INCLUDES EQU.BRN.DETAIL.DIM

INCLUDE INCLUDES EQU.BS.CUSTOMER.RETURN.DIM

INCLUDE INCLUDES EQU.BS.CUSTOMER.RETURN.LINE.DIM

INCLUDE INCLUDES EQU.PF.PRODUCT.MASTER.DIM

INCLUDE INCLUDES EQU.ORDER.LINE

INCLUDE INCLUDES EQU.DOCUMENT.HISTORY

INCLUDE INCLUDES DOCUMENT.HISTORY.PERIODS

INCLUDE INCLUDES EQU.TH-CONTRACT-LINE

INCLUDE INCLUDES EQU.ORDER.HEADER

INCLUDE INCLUDES EQU.RETURN.HISTORY.DIM

INCLUDE INCLUDES EQU.BS.EPOD.DROP.TASK.RESULT.DIM

INCLUDE INCLUDES EQU.BS.EPOD.DROP.RESULT.DIM

INCLUDE INCLUDES EQU.OS.ECOMMERCE.DIARY.DIM

Uc

System - Lines 23 to 30

These files define the structure of business records used throughout the application, including customer information, product data, order processing, returns and contract management.

They provide a common format that allows different parts of the system to work with the same data reliably.

System - Lines 23 to 36

These files define the structure of business records used throughout the application, including customer information, product data, order processing, returns and contract management.

They provide a common format that allows different parts of the system to work with the same data reliably.

Leave Note

Leave Note

Related Code

Related Code

Interactive Dependency Map

Systems Network

1,354,000 nodes · Click a node to focus · Click the focused node for details

Quick jumps

Node types

Program
Orchestration layer
Subroutine
Core processing
Extension
Adjacent services
100%

Displaying -1 / 8 connections

Automated Code Migration

1

2

3

4

5

6

7

8

9

10

11

12

13

14

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

// code > MENU - CASH REFUNDS & RETURNED

PROGRAM.NAME = “BS.GOODS.RETURN.DRV”

INCLUDE INCLUDES OPEN.FILE.PRODUCT.MASTER

INCLUDE INCLUDES OPEN.FILE.RETURN.HISTORY

INCLUDE INCLUDES OPEN.FILE.POS.CUSTOMER

INCLUDE INCLUDES OPEN.FILE.UOM.DETAIL

INCLUDE INCLUDES BUILD.TOP.RIGHT

IF ERR # “” THEN

    FATAL.ERROR.MSG = “CANNOT OPEN FILES”:ERR

    GOSUB FATAL.ERROR

END

EXT.TODAY = OCONV(DATE(),“D2/“)

CURRENT.TIME = OCONV(TIME(), "MTS")

USER.ID = @USERNO

// code > MENU - CASH

REFUNDS & RETURNED

PROGRAM.NAME = “BS.GOODS.RETURN.DRV”

INCLUDE INCLUDES OPEN.FILE.PRODUCT.MASTER

INCLUDE INCLUDES OPEN.FILE.RETURN.HISTORY

INCLUDE INCLUDES OPEN.FILE.POS.CUSTOMER

INCLUDE INCLUDES OPEN.FILE.UOM.DETAIL

INCLUDE INCLUDES BUILD.TOP.RIGHT

IF ERR # “” THEN

    FATAL.ERROR.MSG = “CANNOT OPEN FILES”:ERR

    GOSUB FATAL.ERROR

END

EXT.TODAY = OCONV(DATE(),“D2/“)

CURRENT.TIME = OCONV(TIME(), "MTS")

USER.ID = @USERNO

Uc

UniBasic

1

2

3

4

5

6

7

8

9

10

11

12

13

14

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

// code > MENU - CASH REFUNDS & RETURNED

from dataclasses import dataclass, field

from datetime import date, datetime


class FatalProgramError(Exception):

    pass

@dataclass

class UniFile:

    records: dict = field(default_factory=dict)

    def read(self, key):

        if key not in self.records:

            raise KeyError(key)

current_time = datetime.now().strftime(“%H:%M:%S“)

user_id = getpass.getuser()

// code > MENU - CASH REFUNDS & RETURNED

from dataclasses import dataclass, field

from datetime import date, datetime


class FatalProgramError(Exception):

    pass

@dataclass

class UniFile:

    records: dict = field(default_factory=dict)

    def read(self, key):

        if key not in self.records:

            raise KeyError(key)

current_time = datetime.now().strftime(“%H:%M:%S“)

user_id = getpass.getuser()

// code > MENU - CASH
REFUNDS & RETURNED

from dataclasses import dataclass, field

from datetime import date, datetime


class FatalProgramError(Exception):

    pass

@dataclass

class UniFile:

    records: dict = field(default_factory=dict)

    def read(self, key):

        if key not in self.records:

            raise KeyError(key)

current_time = datetime.now().strftime(“%H:%M:%S“)

user_id = getpass.getuser()

Uc

UniBasic

Python

Incident Intelligence

Ticket Details

Priority

High

Time Remaining

8h remaining

Status

In Progress

novolingo Recommended Fix

novolingo
Recommended Fix

95% Confidence

95%

Add null variable validation for BSO.CORE at line 777 without prior definition.
The system defaults the value to zero, which can cause downstream calculation issues.

Why this fix ?

Affected Service

Branch Stock Control

Predicted Outcome

95% success

Rollback Risk

Low

Generated by novolingo.

2 similar incidents

Start with the problem that matters now.

Tell us what’s getting in the way, what’s at stake and what you want to achieve. We will work out how we can help.

Talk to Mitra

Talk to Mitra