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AI WORKSPACE · CHAT & CODE
Chat and code with the models you want.The governance your business needs.
Chat, create and analyze in one workspace. Switch to Code and it works on your repositories: it reads the project, runs the tests and opens the pull request. Families such as GPT, Claude, Gemini and DeepSeek, with protection rules and visibility into usage.
- Code with SQ Auto or the model you pick, Max Mode for the hard problems, in the ScaleQuality cloud or on your computer.New
- Rules to detect, redact and block data in supported modes.
- Costs, access and limits in the context of your operation, for every conversation and every change.
ScaleQuality / AI Workspace
Summarize this contract. Contact: ana@example.com[EMAIL_REDACTED]
Email protected before sendingAdd rate limiting to the payments API and cover it with tests.
Describe what you need…
Connections
Connect where AI already runs in your company.
Providers, clouds and gateways your teams already pay for. Cost, usage and the rules that apply are measured in one place, from each account's own reports.
Anthropic
OpenAI
Google Cloud
AWS
Databricks
Snowflake
Cloudflare
OpenRouter
LiteLLM
Portkey
Kong
CursorAnthropicOpenAIGoogle CloudAWSDatabricksSnowflakeCloudflareOpenRouterLiteLLMPortkeyKongCursorCODE INTELLIGENCE
Can you trust your code?See the evidence behind the answer.
A diagnosis of code maturity, risks and AI durability. See what holds your project back, follow each finding to its evidence and measure progress.
- Findings tied to the file, line and measured revision.
- Continuous measurement when integrated into your pipeline.
- Priorities that can become corrective actions with agents.
Can I trust this code?
main · a1b2c3dof the code AI wrote survives
b4c5d6eCIMeasureUpdate diagnosisScaleQuality in your coding assistant.Measure, dispatch and follow up without leaving the terminal.
Connect the ScaleQuality MCP to Claude Code, Codex, Cursor or VS Code. Your assistant reads the real measurement of the repository, points at what weighs on the score and dispatches a specialist agent with your plan's credit.
- Real measurement of the connected branch, never the model's estimate.
- The agent opens a pull request with evidence. It never merges.
- Plan usage visible before dispatching. No surprises.
- The models can come from here too: point your coding tool at
SQ Auto and every call follows the company's rules and limits.
WORKS WITH
Claude Code
Codex
Cursor
VS Code
Gemini CLI
WindsurfIllustrative example. Results depend on the organization's access and plan.
AGENTS
Intelligence finds it.Agents move the work forward.
Specialist agents work on demand or autonomously within the scope you authorize. From a finding to a proposed fix, with validation and traceability.
- Autonomy within repositories and limits you define.
- Changes linked to findings and validation results.
- ScaleQuality does not merge pull requests.
Your team controls approval and merge in your provider.
From obligation to pull request.
Controls measured from the code, corrective actions dispatched to an agent, and evidence exported with a manifest. Regulation stops being a spreadsheet.
Regulation or framework
LGPD (Law 13,709/2018), arts. 46 to 49
pack v1.1 · 90-day window · BR
1
Met
5
Partial
0
Missing
3
Manual
Controls with something pending · 5 of 9
No findings matching the specified scanners, domains and severity filter
1 of 18 measured projects without matching findings · 126 open findings in the rest
Illustrative example. Names and numbers are not from a real organization.
01
Controls measured from code
Each control reads the measurement: findings, scanners, coverage and supply chain. Met, partial, missing or manual, with the projects that fail it.
02
Remediate with agent
A pending control dispatches a specialist agent. The pull request stays linked to the control and to the corrective action until your team reviews it.
03
Evidence you can hand over
SBOM per repository, diagnosis reports, AI governance export and a full dossier with a SHA-256 manifest. One observation window, one download.
24 references, scope declared one by one.
Each reference separates what is already implemented from what is being expanded. Being in the catalog is not a certification, and a merged pull request does not mark a control as met on its own.
Confidence to operate. Evidence to decide.
Policies, controls and evidence connected to AI operations.
Explore how messages and code are processed, which providers are involved and the boundaries of each mode in our Trust Center.
SQCM v2.1 · published, citable, with DOI.
The published methodology describes the five domains, where evidence comes from, and when scores can be compared.
Read the white paperA playbook for your next level of engineering.
From diagnosis to the methodology’s Elite level: a path through 12 domains, practices and verifiable gates. Prioritize work that reduces rework, improves operational efficiency and frees capacity to generate revenue.
Cycling through the levels. Click a level to explore it.
Living curation
Domains and gates are revised with periodic market research. Your standard tracks the state of the art, not the date it was written.
Levels can't be bought
A level is the lower of the domain score and the gates met. One strong domain never pays for a missing foundation.
Declared against measured
What the team declares is checked against evidence from your environment. Where evidence disagrees, the domain drops to the floor.
One platform.Two ways to move forward.
Led by your team, or implemented alongside our specialists. Progress measured by ScaleQuality.
ScaleQuality Platform
Your team leads.
Diagnosis, priorities and continuous measurement. Your team uses the platform to decide and implement improvements.
ScaleQuality Managed
We implement with you.
90 days with dedicated specialists, a defined scope and measurable progress in your environment.
Then your team continues with ScaleQuality Enterprise.