risk and maturity for AI products

Your company already has AI running. But has anyone read the code?

Trust Score AI Products technically evaluates systems, automations, agents and software created or accelerated with AI. We read source code, architecture, integrations, data, security, scale and governance to deliver an executive report with evidence: what to keep, fix, pause, restructure or scale.

See risk matrix

Code

technical reading of repository, structure and dependencies

Risk

security, data, scale, governance and continuity

Decision

evidence-based report for leadership action

the real pain

The problem is not using AI. It is not knowing which risk category it entered.

AI accelerates people and teams. What concerns leadership is discovering too late that an automation became a system, a prototype became operation or an almost-SaaS product was born without enough engineering to protect the company.

Teams creating solutions alone

Marketing, operations, support or IT use tools and agents without simple policy, clear owner or audit trail.

Automation becoming system

What started to save time begins touching data, clients, finance, integrations and critical decisions.

Product created too fast

The interface works, but code mixes business rules, data access, integrations and security in the same place.

Scale before governance

The company wants to release, sell or integrate without knowing the real risk.

Trust Score matrix

Classifying usage avoids two mistakes: blocking everything or releasing risk blindly.

The matrix separates AI uses by complexity and risk. Levels 1 and 2 can scale with guidance. Levels 3, 4 and 5 require increasing governance, engineering involvement, technical evidence and a clear owner.

The public classification below shows the executive reasoning. The full evaluation, scoring and technical reading method remains protected inside the product.

Content and communication

Documents, reports, presentations, emails, images and posts. If it fails, it can be reviewed.

reportspresentationscommunication

Quem opera?

all teams

Risco: low

Simple visual interface

Pages, landing pages, prototypes and dashboards without complex authentication or sensitive data.

landing pagesprototypesdashboards

Quem opera?

teams + checklist

Risco: low/medium

Internal-use tool

Internal automations, task controls, bots and agents that start affecting productivity.

automationstasksagents

Quem opera?

team + IT review

Risco: medium

Business system

Touches client, employee, financial, integration, permission or operational logic data.

personal dataintegrationsreal operation

Quem opera?

IT + data + security

Risco: high

Product / critical infrastructure

SaaS, white-label, multi-company, critical infrastructure or product sold to third parties.

SaaSwhite-labelmulti-tenant

Quem opera?

central technical team

Risco: critical

strategic diagnosis

The 6 questions that need answers before scaling.

Trust Score does not answer by opinion. Every conclusion must come with technical evidence, impact reading and decision recommendation.

question 01

Who governs this system inside the company?

owner, trail and responsibility

We identify whether there is technical ownership, documentation, tests, responsibility separation and traceability for safe continuity.

question 02

If the creator leaves, what is the impact?

continuity and bus factor

We evaluate person dependency, knowledge concentration, code organization and real maintainability by another professional or squad.

question 03

Can this become a product, SaaS or B2B?

the proposal may be good and the base may not

We separate business value from technical readiness. A strong idea may still require architecture, data isolation and governance before being sold.

question 04

Can the system scale?

capacity, queues and operation

We look for processing bottlenecks, memory usage, service dependency, infrastructure limits and breaking points under growth.

question 05

Does the system protect the company?

security, data and privacy

We read authentication, permissions, keys, exposed routes, credential storage, sensitive data and active financial or legal risk.

question 06

Does it generate real value or future debt?

both can be true

The report recognizes what works and shows what needs correction. The goal is not to kill a good initiative, but to prevent real value from becoming liability.

technical reading

The report reads the product from the inside, not just the presentation outside.

Trust Score connects executive view with engineering. Leadership understands risk in business language; the technical team receives enough evidence to act.

Source code

structure, coupling, critical files, dependencies, patterns and signals of generation without review.

Architecture

responsibility separation, layers, backend, integrations and evolution capacity.

Security

authentication, authorization, keys, exposed routes, secrets, permissions and sensitive data.

Data

modeling, access, isolation, privacy, traceability, history and information quality.

Scale

infrastructure limits, queues, concurrency, costs, bottlenecks and single points of failure.

Governance

owner, documentation, tests, CI/CD, monitoring, technical roadmap and continuity.

deliverables

You receive a report for decision, not a loose list of problems.

The delivery combines CEO, founder, CTO, product and engineering views. It shows where value exists, where risk exists and which move comes first.

Executive summary

direct diagnosis for leadership to decide whether to keep, fix, pause, restructure or scale.

Complexity and risk matrix

classification across the 5 AI usage levels, with required governance reading.

Technical scorecard

pillar assessment such as architecture, code, data, backend, security, tests and DevOps.

Risk map

findings prioritized by impact: critical, high, medium or low, with business consequence.

Value versus debt

what the solution already proved and what must be corrected to avoid liability.

Evolution roadmap

practical sequence for correction, protection, restructuring and responsible scaling.

possible decision

After Trust Score, the conversation stops being opinion.

Leadership starts seeing the product as asset, risk or evolution opportunity. This changes decision quality before investing more time, money and reputation.

Keep

when the solution is simple, useful and risk is acceptable.

Fix

when there is real value, but technical or security points need action.

Pause

when current use exposes data, operation or costs before minimum control exists.

Restructure

when the proposal is good, but the technical base blocks scale, maintenance or sales.

Scale

when there is evidence of value, enough governance and a technical path to grow.

when it fits

Hire Trust Score when AI has left the lab.

a team created automation or an agent and now wants to release it to more people

a prototype became a system used in operation

a fast-created product must become SaaS, B2B or white-label

the CEO wants to know if it protects data, scales and deserves investment

the CTO needs evidence to prioritize correction, refactoring or rebuild

the company wants to reduce risk before connecting more data, clients and integrations

FAQ

Common questions

Is Trust Score a code audit?

Yes, but not only that. The solution reads code, architecture, data, security, governance and business impact to turn technical analysis into executive decision.

Does the report expose the team that built it?

No. The goal is not blame. It is protecting the company, recognizing real value and showing the next step with evidence.

Do you evaluate systems created with AI by non-technical teams?

Yes. This is one of the main scenarios: useful solutions created fast, but without clarity on risk, scale, ownership, security or continuity.

next step

Before scaling an AI-built solution, discover what it really carries.

Talk to Tech Human to evaluate whether your system, automation, agent or product needs Trust Score before it grows.

Solutions