Operational Quality Intelligence

Manage reality, not the plan.

From the moment a task is opened until the PR is merged, OpsQI analyses every step end to end with AI — and shows bottlenecks, burnout risk and quality drift before you notice them.

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No credit card · AI included, no setup · Turkish and English

AI layer

  • Burnout risk · 2 signals
  • Task quality · red
  • SPI 0.86 · behind schedule

What we guarantee

  • Full Turkish and English interface
  • 6 system roles + custom roles, permission-based access
  • Audit log (7 days – 1 year retention by plan)
  • AI included — no separate key or setup
  • Self-hosted GitLab, GitHub and Bitbucket support

How it works

Scattered data → layered signals → one truth.

  1. 01

    Collect

    Tasks, workflows, PRs/MRs, files, communication, expenses and meetings live in one workspace, each protected by role-based permissions.

  2. 02

    Understand

    Background AI processors and scheduled analyses continuously recompute task quality, project health, SPI/CPI and workload.

  3. 03

    Alert

    When a risk threshold is crossed, the right person is notified — team lead, department manager or CTO. A morning briefing summarises the day.

Role-based

Four questions, four screens.

Everyone looks at the same data, but sees the answer to their own question.

Bottleneck Radar

Risky projects, people bottlenecks, blockers, open escalations and a department rollup on one screen.

Illustrative view

  • Risky project · Mobile App v3
  • Bottleneck · 11 active tasks on 1 person
  • Open escalation · Workload (2)

End-to-end AI

Every task, every PR, every thread goes through AI.

OpsQI doesn't just collect data; it analyses every step of the work lifecycle with AI. You only see the result and the next step to take.

AI across the work lifecycle

  1. 01

    A task is opened

    AI

    Scope and description quality analysis, technical conflict check; quality (drift) score

  2. 02

    Code is written

    AI

    Automatic review on every PR/MR, inline comments and fix suggestions

  3. 03

    The team talks

    AI

    Thread and document summaries, OCR, response-time analysis

  4. 04

    The project moves

    AI

    Daily health score, SPI/CPI, burnout and bottleneck signals

  5. 05

    A manager decides

    AI

    Morning briefing, risk alerts and an AI Assistant that answers from your documents

AI processors running in the background

  • Task analysis

    Assesses a new task's scope, description quality (clarity, acceptance criteria, scope, context) and technical conflicts with existing work.

    Input
    “Add real-time notifications to the dashboard”
    Example output
    Description quality 45/100 · acceptance criteria missing

  • Task quality (drift)

    Compares a task semantically with the project's last 20 tasks and turns 8 signals into a 0–100 score.

    Input
    Vague task flagged “urgent”
    Example output
    Drift 74 · red · PM notified

  • Bug matching

    Compares a new bug with past records and flags likely duplicates.

    Input
    “500 error on the payment page”
    Example output
    Similar record found · link to previous fix

  • Summarisation

    Turns long documents and threads into a short executive summary.

    Input
    Long team thread
    Example output
    Decision · timeline · open blocker

  • Communication summary

    Turns every call, email and meeting record into a 2–3 sentence summary.

    Input
    Notes from a 45-minute customer meeting
    Example output
    Decision · open issue · next step

  • OCR

    Makes Turkish and English text in scanned documents and images searchable.

    Input
    Scanned contract appendix
    Example output
    Searchable text + summary

  • Pool analysis

    Reads a new request and extracts critical points, scenarios, a recommended team, priority and a week-by-week plan.

    Input
    New tender request with attached specification
    Example output
    Recommended team · high priority · ~6 weeks

  • AI Assistant

    Answers from your workspace files using RAG, grounded in sources.

    Input
    “Does the contract have a late-delivery penalty?”
    Example output
    Sourced answer · link to the file

AI included. No setup.

We provide and operate the model. No API key, model choice or extra setup; AI usage is included in your plan's monthly request limit.

AI and data policy

Only in OpsQI

Measures what other tools don't.

  • Task quality drift score

    Semantic drift, priority inflation, impossible dates, workflow violations — see your backlog decay before it happens.

  • Early burnout warning

    Alerts managers when workload, clustered deadlines and performance drops coincide.

  • Escalation & DipNot

    A recorded channel for mobbing, workload and process issues; notes up or down the hierarchy.

  • Fair performance + appeals

    Role-based weights, scoring presets, an approval step and an appeal process.

  • Meeting cost

    Calculated from participants' hourly cost and booked to the project as an expense.

  • See all 20 modules

AI code review

From PR to task, from finding to fix.

GitHub, GitLab and Bitbucket — including self-hosted instances. Connect with a PAT or OAuth.

  1. Connect

    Connect a repository; every PR/MR enters review automatically via webhook.

  2. Review

    Summary, inline comments and commit status are written straight to the PR/MR.

  3. Fix

    Per-finding or bulk fix suggestions; optionally open a separate fix PR.

  4. Link

    Reviews are linked to tasks; quality signals flow into reports.

Security

Clear answers to the questions enterprise teams ask.

Security details

  • Workspace isolation

    Requests without a workspace context are rejected (fail-closed).

  • Permission-based access

    6 system roles, custom roles and granular permission keys.

  • Audit log

    Who changed what, and when — retention by plan.

  • Encrypted credentials

    Git credentials are stored with AES-256-GCM.

Plans

Start free, upgrade as your team grows.

Compare plans

  • Free

    For small teams and trials.

    Free

    Up to 5 users

  • Pro

    For teams starting to measure quality and performance.

    From $12 / user / month

    Up to 25 users

  • Ultra

    For organisations running multiple departments.

    From $20 / user / month

    Up to 100 users

  • Custom

    Custom limits and requirements.

    Get a quote

    Tailored

Frequently asked questions

How is OpsQI different from Jira or Monday?

Those tools manage the plan. Alongside the plan, OpsQI measures the reality of the work: it automatically computes signals like task quality (drift), burnout risk, project health, SPI/CPI and code review quality, and alerts the right person.

Can I start for free?

Yes. When you sign up, your workspace starts on the Free plan: 5 users, 3 active projects and 25 AI requests per month. No credit card required.

How do I move to a paid plan?

Online payment isn't active yet. To move to Pro, Ultra or Custom, contact our sales team and we'll switch your plan for you.

Do I need to set anything up for the AI?

AI is included in OpsQI; we provide and operate the model. No separate API key or setup is needed. AI usage is measured against your plan's monthly request limit.

Does it work with self-hosted GitLab?

Yes. GitLab, GitHub and Bitbucket connections accept a custom server URL. For self-hosted GitLab we recommend a personal access token (PAT).

What are SPI and CPI?

The Schedule Performance Index (SPI) measures schedule efficiency and the Cost Performance Index (CPI) measures budget efficiency. 1.0 or above means on track; below means behind. OpsQI computes both daily with project health; CPI uses real hourly cost.

See it with your own data.

Open a free workspace, or let's schedule a demo with your team.

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