The AI
Software Factory

A delivery system where AI handles the routine work and your people hold the decisions.

AI automated Human approval
  1. 1User feedback
  2. 2Triage & plan
  3. 3Prioritize
  4. 4Approve
  5. 5Build & test
  6. 6Sign-off
  7. 7Promote & log

Continuous auditable process

How to start

Facienta Consulting deploys a three-phase roadmap to adoption, starting with a six-week assessment.

Find out more

Business impact

Measured gains across cost, speed and quality

40–50%Faster development cycles
30%+Lower cost to deliver
50%Fewer defects reaching production
2–3×Faster onboarding for new engineers

Observed ranges across comparable delivery programs

How it runs

From feedback to production in seven steps

An automated loop with human approval at the decision points.

1

User submits feedback

In-app button reports a bug or requests an enhancement.

2

AI registers and triages

Logged and scored for impact, severity, size and complexity.

3

Gate 01 · Human approval

Product owner reviews

Prioritizes the request; if selected, AI drafts the delivery plan.

4

Gate 02 · Human approval

Engineering approves

Plan is edited and signed off on technical approach.

5

Two AI bots launch

One builds the change, the second builds and runs the tests.

6

Gate 03 · Human approval

Joint review and sign-off

Code and test results go to Engineering and Product to promote.

7

Automated promotion

AI raises the change request and promotes the fix to production.

Change is live — the user is notified

Every step is logged: a full audit trail from request to release.

Governance

Three gates where a person still decides

Gate 01 · Step 3

Product owner prioritizes

Nothing enters the build queue without a business decision on value.

Gate 02 · Step 4

Engineering approves the approach

The technical plan is edited and owned by your engineers, not the model.

Gate 03 · Step 6

Joint sign-off before production

Product and Engineering review the code and test evidence together.

Adoption roadmap

Three phases from audit to scale

01

Assessment

Weeks 1–6

  • Audit current delivery processes
  • Identify automation opportunities
  • Set baseline metrics

02

Pilot

Weeks 7–18

  • Select one pilot team and product
  • Implement the MVP
  • Measure against the baseline

03

Scale

Quarter 2 onward

  • Expand to all delivery teams
  • Optimize workflows and gates
  • Drive continuous improvement

Next steps

Start with the six-week assessment

One team, one baseline, no change to your production pipeline until Phase 2.

Book the assessment

We need from you

A product owner and an engineering lead

You get back

A baselined opportunity map and pilot plan

About

fa’cient/

noun. a doer; an agent.

suffix. causality; created by people to expand meaning.

Specialized teams, deployed to deliver

Right-sizing has left most organizations staffed for standard operations, not for strategic initiatives. When one lands, it either calls for skills the business unit does not have, or it goes to people already carrying a full workload — putting the initiative and the day job at risk.

Facienta deploys specialized teams into the organization to execute specific, defined projects. We can extend your existing team or own the delivery outright. Every engagement starts with a clear reading of the intended impact, and ends with the results embedded in your organization.

Each project closes with the education, training and knowledge your people need to manage, maintain and keep improving what was built. Facienta works with clients in the United States and Europe.

Services

Three practices, one way of working

Process re-engineering

Map it, redesign it, close the gap

  • Document current processes and the resources at each stage — roles, organic functions, managing systems
  • Define the future-state process for optimal results
  • Run a gap analysis between current and future state
  • Produce a roadmap to reach the optimal process

BI & predictive analytics

From raw data to decisions people trust

  • Definition of analytics initiatives and goals
  • Datasource identification, analysis and preparation — cleansing, normalization, optimization, logical views
  • Machine-learning models that forecast demand, churn and risk from your own historical data
  • Natural-language querying, so business users interrogate the data without writing SQL
  • Anomaly detection with automated alerting on the metrics that drive decisions

AI Software Factory

Delivery as a governed pipeline

  • Build, test, deploy and monitor joined into one flow — not a set of disconnected tools
  • Routine work automated so your engineers move to the decisions that need judgement
  • Three approval gates where Product and Engineering own the call
  • A full audit trail from request to release
See how it runs

Contact

Let’s talk

Interested in how Facienta can enact change in your organization?

Email us

Direct

info@facienta.com