CASE STUDY/GLOBAL PAPER MANUFACTURER

>60%+ faster SAP performance, no manual rework

Autonomous AI transformed DB-bound custom ABAP into scalable, HANA-optimized execution cutting runtime by more than half for one of India’s largest paper manufacturers.

Pattern
PERFORMANCE
60%-80%faster
MANUAL ABAP EFFORT
ZERO
DELIVERY VELOCITY
1 hourvs 1 week
GST & FINANCE REPORTING
100%restored and stable
THE CHALLENGE

Aging Custom ABAP Undermining SAP ECC Performance

As part of ongoing SAP modernization efforts, the organization identified performance limitations across several custom ABAP programs running on SAP ECC.

Over time, these programs had accumulated legacy coding patterns that were not optimized for HANA-based execution. As data volumes increased, program runtimes degraded, impacting the reliability and responsiveness of critical financial and reporting workloads.

Traditional remediation approaches required manual refactoring of each program, with estimates of one to two weeks of effort per object. This approach depended heavily on specialized ABAP expertise and introduced delivery risk, making large-scale optimization difficult to execute efficiently.

Refactoring these programs manually would have required weeks of effort per object.

- IT Lead, Paper Manufacturer
THE APPROACH

End-to-End SAP Optimization Powered by Autonomous Agents

Sookti AI deployed autonomous agents to analyze and optimize the client's most resource-intensive custom SAP programs.

The agents:

Analyzed execution paths to identify inefficient legacy patterns
Automatically transformed existing logic into HANA-optimized ABAP structures
Applied clean-core-aligned coding practices by default
Validated outputs through automated regression testing to ensure accuracy

Each program was modernized end to end by the agents, with no human intervention required. All changes were validated to ensure identical functional output before deployment.

THE RESULTS

Runtime & Execution Metrics (SAP SAT – Live Workloads)

PROGRAM / REPORT
ZFI_GST_INPUT_REGISTER Net Runtime
BEFORE (LEGACY)
~19.1sec
AFTER (SOOKTI AI)
~7.1 sec
IMPROVEMENT
~63%reduction
PROGRAM / REPORT
Database Time
BEFORE (LEGACY)
~78.5%
AFTER (SOOKTI AI)
~56 %
IMPROVEMENT
DB dominancereduced

Execution shifted from DB-bound, row-based access to balanced, HANA-aligned processing.

CUSTOM CODE REFACTORED
15000lines
STABILITY
ZEROregressions
OPERATIONAL RISK
100%eliminated
DOCUMENTATION
Automatic& audit-ready
WHAT CHANGED

HANA-Optimized Bulk Retrieval

Before
SELECT * in LOOP
LOOP AT it_gst ASSIGNING FIELD-SYMBOL(<fs>).
  " Performance hit: SELECT * inside loop
  SELECT SINGLE * FROM bseg INTO @DATA(wan_bseg)
    WHERE bukrs EQ @<fs>-rbukrs AND belnr EQ @<fs>-belnr
      AND gjahr EQ @<fs>-gjahr AND lifnr EQ @<fs>-lifnr
      AND koart EQ 'K'.
ENDLOOP.
After
CDS View + Binary Search
IF it_gst IS NOT INITIAL.
  " Optimization: FOR ALL ENTRIES with specific columns
  SELECT bseg_bukrs, bseg_belnr, bseg_gjahr, bseg_lifnr,
         bseg_shkzg, bseg_hsn_sac, bseg_txgrp
    FROM zfi_gst_input_1 
    INTO TABLE @DATA(lt_gst_data)
    FOR ALL ENTRIES IN @it_gst
    WHERE bseg_bukrs = @it_gst-rbukrs.
  
  SORT lt_gst_data BY bseg_bukrs bseg_belnr bseg_gjahr bseg_lifnr.
ENDIF.

LOOP AT it_gst ASSIGNING FIELD-SYMBOL(<fs>).
  " Binary Search instead of DB hit
  READ TABLE lt_gst_data INTO DATA(wan_bseg)
    WITH KEY bseg_bukrs = <fs>-rbukrs
    BINARY SEARCH.
ENDLOOP.

The agent automatically switched from standard tables to performance-optimized CDS views, pre-loading data in bulk rather than per-record.

ENGAGEMENT DETAILS

Aspect Details

Industry
Manufacturing (Paper)
Landscape
SAP ECC S/4HANA (Brownfield)
Timeline
1 hour vs 1 week previously
Delivery Partner
SGN Software

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