For AI platform leaders

Move the workload. Keep the context.

Separate your organization's context from the models and agent products that execute the work. Define context once, then use it across your agent stack.

Book a platform walkthroughSee the portability problem

Works natively inside:

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Every agent product creates another context silo.

  1. Duplicate stacks

    Every runtime needs its own context setup

    Platform teams rebuild instructions, Skills, memory, permissions, and policy delivery for each model, agent product, custom app, and execution environment.

  2. Translation tax

    Shared context becomes product-specific configuration

    One source turns into several formats, sync scripts, and local adapters. Every change creates another chance for drift.

  3. Policy drift

    A platform switch changes more than the model

    The new runtime may receive different standards, Skills, and working history, so evaluation results mix model quality with missing context.

  4. Switching cost

    The best context becomes a reason not to move

    Teams stay on a product because years of instructions and workflows are trapped there, even when cost, quality, or risk says the workload should move.

Platform policyAGENTS.md
Workflow packageSkill
Domain contextMemory
Codingagent
Webagent
Customagent

Make context a platform layer of its own.

Alignbase gives your organization a governed source for context, including AGENTS.md guidance, Skills, Memory, and policy. Supported integrations request the right bundle, so context does not have to live inside one model or agent product.

Define context once

  • Company and platform policy
  • Domain and product knowledge
  • Reusable workflow Skills
  • Short-term Memory for active work

Route by workload

  • User, team, project, and environment
  • Agent and integration type
  • Task-specific Skill access
  • Permissions for read, write, and publish

Keep the control plane stable

  • Versioned sources independent of the runtime
  • One review and publication model
  • Point-in-time distribution records
  • Adapters for supported agent products

Change the execution layer without losing the operating layer.

  1. Multi-vendor
    73%
    of surveyed executives describe their AI environment as intentionally multi-vendorIBM Institute for Business Value and Oxford Economics (2026). In a survey of 1,000 senior executives across 16 countries and 17 industries, 73% described their AI environments as intentionally multi-vendor. IBM notes that business-unit decisions and geography often drive that mix.Read the source

    Support the stack your business already has

    Manage shared context above the products selected by different teams, regions, and use cases.

  2. Switchable
    71%
    of surveyed executives say switching a main AI vendor or model is difficultIBM Institute for Business Value and Oxford Economics (2026). In a survey of 1,000 senior executives across 16 countries and 17 industries, 71% said switching their primary AI vendor or model would be difficult.Read the source

    Move workloads without rebuilding their context

    Keep durable policy, domain knowledge, and workflow packages separate from the model or agent that runs them.

  3. Visible
    91%
    say they do not fully understand their AI dependenciesIBM Institute for Business Value and Oxford Economics (2026). In a survey of 1,000 senior executives across 16 countries and 17 industries, 91% said they did not fully understand dependencies across AI vendors, models, and infrastructure.Read the source

    See dependencies in one governed layer

    Tie agents, integrations, context versions, and access scope together instead of tracing product-specific configuration by hand.

  4. Adaptable
    10%
    higher reported AI ROI among organizations designed early for adaptabilityIBM Institute for Business Value and Oxford Economics (2026). In survey analysis of 2,000 senior technology executives, organizations designed early for portable workloads and replaceable models reported 10% higher AI return on investment in 2025. This is an association in self-reported survey data, not a causal estimate.Read the source

    Keep context stable while the stack changes

    Evaluate models and products against the same governed inputs, then move execution without moving the source of truth.

Start with one workload that may need to move.

Choose a workflow used across more than one model, product, or runtime. Pull its shared context into one source, then connect the execution paths you want to support.

  1. Step 1

    Separate context from runtime config

    Move durable policy, domain knowledge, Skills, and working Memory into a governed repository.

  2. Step 2

    Connect supported execution paths

    Route the right bundle to web agents, coding agents, or custom agents based on user, scope, and task.

  3. Step 3

    Evaluate and move with the same inputs

    Keep context versions stable while you compare or switch the model and product that execute the work.

CompanyStrategy
EngPolicies
SalesPolicies
Division 1KPIs
Division 2KPIs
Team AArchitecture
Team BArchitecture

Own the context layer your agent stack depends on.

See how Alignbase can keep context portable while models, products, and workloads change.

Book a platform walkthrough
Questions AI platform leaders ask.

How portability, integrations, governance, evaluation, and migration work.

What does portable context mean?
It means your organization's source for instructions, Skills, Memory, policy, and domain knowledge is independent of one model or agent product, then delivered through supported integrations.
Does Alignbase make every vendor format identical?
No. Agent products expose different integration points and capabilities. Alignbase keeps the governed source stable and uses integrations to deliver the context each supported product can accept.
Can we use Alignbase with custom agents?
Yes. Custom and pull-based integrations can request current context, discover available Skills, and use the same tag, permission, version, and audit model as other connected agents.
How does this help model evaluation?
You can hold the context version and access scope constant while changing the execution layer. That makes it easier to separate model or product differences from missing or stale inputs.
Does Alignbase orchestrate agent tasks?
No. Alignbase governs and distributes the context agents need. Your orchestration and execution systems still decide which agent runs, which tools it calls, and how the workload proceeds.
Where should a platform team start?
Pick one valuable workload that already crosses products or may need to move. Centralize its shared context, connect two execution paths, and test whether both receive the same approved inputs.