From AI experiments to standard practice.

Taivala - the AI engineering control plane that makes AI-assisted workflows repeatable and measurable across your org - without replacing your stack.

Lead your teams from isolated copilots to an AI-native operating model.

Contact us See how it works

Why AI initiatives stall

AI tools spread faster than governance and proof. Without standard workflows and in‑flow policy, wins stay local and risk stays invisible.

Wins stay isolated

Local experiments thrive, but without shared playbooks and paved paths they never scale across the org.

Trust gaps block rollout

Risk teams lack approvals, least‑privilege actions, and audit trails—so leadership hesitates to greenlight AI.

Policy lives on paper

Guidelines in docs don’t change behavior; enforcement has to sit inside IDEs, chat, and CI.

Stack stays fragmented

Copilots and agents pile up without a control plane to orchestrate how they hit your internal platforms.

Platforms feel brittle

Teams need consistent guardrails across repos, pipelines, and envs—not another mandate to swap tooling.

Prompts don’t scale

Individual prompting hacks never become shared workflows, so org-wide improvements stall.

What is Taivala

A control plane that standardizes AI‑assisted engineering—enabling repeatable workflows, policy enforcement, and measurable improvement across teams.

DX‑first onboarding

SSO, extensions, and organizational context land in minutes so every developer’s IDE and chat assistant knows your playbook from day one.

  • VS Code & JetBrains extensions with guided install
  • Slack & Teams assistants tuned to your platform capabilities
  • Technology strategy and standards delivered as MCP resources
  • Provisioning templates to roll out safely across teams

Context + Action Registry

Codify strategy, preferred tech, and guardrails as an MCP resource paired with least‑privilege actions in the flow of work.

  • Engineering context surfaced to every developer
  • Guidance injected into IDE/chat assistants via MCP resources
  • Scoped credentials with approvals & policy packs
  • Event‑level audit export to your systems

Rollout & measurement

Launch playbooks, monitor change, and prove impact with insight into both action usage and how org context is applied across delivery.

  • Adoption by team/repo with guardrail adherence
  • Cohort comparisons and experiment tracking
  • Executive snapshots, KPI exports, and audit signals
  • Feedback loops to refine context + actions continuously

How it works (1‑2‑3)

  1. Connect Taivala — SSO, repositories, chat, and CI wire up so organizational context and policy are synchronized.
  2. Work inside your tools — Developers see strategy, guidelines, and approved actions in IDE/chat with guardrails enforced automatically.
  3. Measure & iterate — Roll out cohorts, track adoption, export audit signals, and continuously refine context plus actions.

What changes in how your teams work

Concrete before/after workflow changes you’ll notice in your existing tools—no rip‑and‑replace.

Incident Ops

Incident follow‑ups get done

Before: Post‑incident actions linger; tests/docs/alerts drift; owners forget.

After: On incident closure, linked issues and draft PRs are created for fixes, tests, docs, and alerts; owners nudged in Slack/Teams until done.

Where: PagerDuty/incident timeline, linked issues & PRs, Slack reminders.

PR Quality

Reviews with fewer cycles

Before: Standards gaps caught late.

After: PR pre‑check suggests fixes (API shape, tests, docs) or raises auto‑fix PRs.

Where: PR checklist, comments, CI.

Feature Flow

Feature flow runs smoother

Before: Manual ticketing and handoffs.

After: Tasks scaffolded, branch created, approved patterns reused, tickets/docs updated.

Where: Issues, branches, linked PRs.

Onboarding

Onboarding to first PR day one

Before: Days of setup.

After: SSO + IDE plugin provide a guided “first change” path with guardrails.

Where: IDE walkthrough, starter PR.

Exec Updates

Status updates write themselves

Before: Reporting tax.

After: Weekly summary compiled from merged PRs/issues/incidents to Slack/Teams.

Where: Slack/Teams post; brief.

Standards

Standards drift prevented

Before: Drift accumulates; big refactors.

After: Guardrails prompt approved patterns; small refactor PRs gated by approvals.

Where: PR suggestions, audit.

Architecture & security

Control plane across IDE/chat/CI with policy enforcement and audit. Built for enterprise safety from day one.

Before

Teams wire AI tooling directly into every surface—each IDE, bot, pipeline, and data source—so governance, policy, and audit have no single insertion point.

IDE Chat Ops CI/CD Prod Access Secrets Data Warehouse Issue Tracker Observability LLM APIs

After

Taivala becomes the control plane: developers stay in their tools, while all actions route through policy, guardrails, and audit before touching your stack or model providers.

Developers

IDE plugins, chat assistants, workflow hints delivered in the flow of work.

Taivala Control Plane

Policy packs, approvals, action registry, telemetry, and audit streaming.

Your Stack

Source, CI/CD, tickets, docs, environments—integrated with least-privilege actions.

LLM Providers

OpenAI, Anthropic, Bedrock, in-house models—brokered through your tenancy & keys.

Security & privacy defaults

No code retention

We don’t store your code. Prompts redacted; logs are metadata‑only.

Customer‑controlled keys

Your vault/KMS; bring your LLM (Azure OpenAI, Bedrock, Vertex).

Scoped permissions

Repo/env/team scoping with approvals; least‑privilege by default.

Exportable audit

Event‑level audit stream to your SIEM (e.g., Splunk/Datadog).

Integrations & compatibility

Connect your stack in minutes—no rip‑and‑replace.

GitHub GitLab Bitbucket VS Code JetBrains Slack Teams Jira Linear CircleCI GitHub Actions Argo PagerDuty Azure OpenAI Amazon Bedrock Google Vertex AI

Ready to make AI standard practice?

See the operating model in action—no rip‑and‑replace, guardrails included.

Fill in the form, book a meeting, or just email us at contact@taivala.com.