Optimize post merger technology integration portfolio

What it's for

Gives acquirers a technology integration frontier: what to retain, bridge, migrate, integrate or retire to preserve standalone value and realize synergy without hiding platform tail risk or scarce capacity.

What you give it

Inputs split into evidence read from your connected systems, calibration your team owns, and numerical controls that affect precision but never the result's meaning.

{
  "capabilities": [
    {
      "annual_synergy_value_scenarios": [
        200000,
        150000
      ],
      "asset_count": 20,
      "direct_loss_per_failure_scenarios": [
        20000,
        60000
      ],
      "id": "billing",
      "maximum_residual_failure_probability": 1,
      "platform_group_id": "target-core",
      "required_control_ids": [],
      "residual_risk_prior_alpha": 3,
      "residual_risk_prior_beta": 17,
      "standalone_value_scenarios": [
        300000,
        250000
      ]
    },
    {
      "annual_synergy_value_scenarios": [
        200000,
        150000
      ],
      "asset_count": 20,
      "direct_loss_per_failure_scenarios": [
        20000,
        60000
      ],
      "id": "identity",
      "maximum_residual_failure_probability": 1,
      "platform_group_id": "target-core",
      "required_control_ids": [],
      "residual_risk_prior_alpha": 3,
      "residual_risk_prior_beta": 17,
      "standalone_value_scenarios": [
        300000,
        250000
      ]
    }

What you get back

This is the actual output of running the example above — computed by the same function the platform calls, not an illustration.

{
  "assumptions": [
    "Each target capability has one complete executable retain/bridge/migrate/integrate/retire menu with prospectively validated failure, detection, remediation, duration, value-retention and synergy effects on one horizon and currency basis.",
    "Platform-group value is unique and counted once under common failure; direct asset failures, controls, cross-option relations, full costs, budget and scarce resources are complete and decision-relevant."
  ],
  "baseline_current_state": {
    "expected_net_value": 123990,
    "expected_total_loss": 412070,
    "loss_conditional_value_at_risk": 2756400,
    "selected_option_ids": [
      "billing-retain",
      "identity-retain"
    ]
  },
  "capability_diagnostics": [
    {
      "action_type": "integrate",
      "capability_id": "billing",
      "expected_residual_failures": 0.1325,
      "residual_failure_probability_by_scenario": [
        0.0743,
        0.3083
      ],
      "selected_option_id": "billing-integrate"
    },
    {
      "action_type": "integrate",
      "capability_id": "identity",
      "expected_residual_failures": 0.1285,
      "residual_failure_probability_by_scenario": [
        0.0712,
        0.2932
      ],
      "selected_option_id": "identity-integrate"
    }
  ],
  "decision": "implement_selected_post_merger_technology_integration_portfolio",
  "economics": {
    "expected_common_platform_loss": 3250,
    "expected_direct_failure_loss": 19220,
    "expected_net_value": 1248697.75,
    "expected_operating_cost": 11995,
    "expected_realized_synergy_value": 814713.75,
    "expected_retained_standalone_value": 568449,

How it works

Constrained optimization — Pick the best feasible option under real limits — budget, headcount, dependencies, capacity — rather than ranking a list and hoping it fits.

1. 1 Simulate capability failures from governed Beta priors and coherent scenarios, then apply each option's prospectively validated failure ceiling, detection, remediation, duration, value retention and synergy realization.
2. 2 Count direct residual failures per asset and each target platform's common value once through joint detection survival; enforce controls, option dependencies/exclusions, budget and scarce resources as hard gates.
3. 3 Select one retain/bridge/migrate/integrate/retire option per capability by expected net value minus loss CVaR, disclose exact or deterministic-beam certainty and return the nondominated frontier against current state.

Before you trust it

Every tool in the catalog ships with the conditions under which its answer is meaningful — and the conditions under which it should abstain instead of guessing.

Calibrating it to your org

Calibration workflow

1. 1 Define the management decision, target outcome, aggregate unit, privacy boundary, cadence, and prediction/intervention horizon for this organization.
2. 2 Build a tenant-scoped historical cohort using only information available before each prediction or decision; preserve zero periods, censoring, assignment probabilities, and unresolved outcomes when the method requires them.
3. 3 Estimate statistical parameters on training history, but obtain costs, utilities, risk tolerance, practical-effect thresholds, capacity, and policy constraints from accountable decision owners.
4. 4 Validate on later time windows or held-out aggregate units at the deployment grain, against a simple baseline and the function-specific validation strategy.
5. 5 Deploy only if the returned decision clears evidence, overlap, calibration, robustness, and guardrail checks; warning, unsupported, schema-gap, and fallback decisions are abstentions.
6. 6 Monitor realized outcomes, data drift, coverage, and decision regret; recalibrate at a governed cadence or after a detected regime/definition change, never merely because a stakeholder dislikes the result.

Call it from your AI

You don't wire up 388 tools in your MCP client. The GitRevio MCP server exposes 18 tools, three of which let an agent search the catalog, read a tool's schema, and run it — so the assistant finds this one on its own.

gitrevio_capabilities_search
  { "q": "choose retain bridge migrate integrate or" }
  → finds "optimize_post_merger_technology_integration_portfolio"

gitrevio_capability_describe
  { "capability_id": "optimize_post_merger_technology_integration_portfolio" }
  → returns the input schema and agent guidance shown on this page

gitrevio_capability_run
  { "capability_id": "optimize_post_merger_technology_integration_portfolio", "arguments": { ... } }
  → returns the result shown above

Works in Claude Desktop, Claude Code, Cursor, Cline, Continue.dev, Goose and Aider. See the MCP server.

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