Engineering Velocity
at Portfolio Scale

We help small and mid-market private equity firms use technology, data, and AI to improve performance, accelerate growth, and create measurable value. Our teams deliver practical solutions that support portfolio-wide transformation, from assessment through execution.
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Technology investments that create portfolio-wide value

Forte Group embeds AI-augmented engineering teams directly inside PE portfolio companies, diagnosing the real bottleneck, building working proofs with real data, and standing up the operating model that turns AI investment into measurable engineering, operational, and product outcomes. Fixed-cost entry points. Sprint-based delivery. Senior practitioners who stay involved.

Where Forte Group's AI capabilities create portfolio value

Four categories of AI-driven impact, applied across every portfolio company.

AI-augmented engineering

An agentic PDLC where AI proposes at every stage and human practitioners approve the gates. Measurable improvements in velocity, quality, and cost , not pilots, production.
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AI-optimized operations

Automate repetitive workflows across HR, Finance, IT Support, Compliance, and customer-facing operations. Reduce manual effort while improving accuracy and auditability.
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AI-enabled product

Embed intelligence directly into the products your portfolio companies sell , conversational AI, recommendation engines, predictive features, dynamic pricing.
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AI transformations

Move portfolio companies from scattered AI experiments to a governed program with measurable ROI targets. Give the board and the PE sponsor a clear framework for where to invest, what to scale, and what to stop.
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Three ways to start
Every engagement begins with a fixed-cost, time-boxed entry point. No open-ended discovery. No surprise invoices.

Diagnostic + Proof Sprint

Mode 1

For portfolio companies where a performance gap is visible but the path forward isn't. In 2–4 weeks, a senior SWAT team diagnoses the real bottleneck, builds a working proof-of-concept on real data, and gives leadership the evidence to commit , or the evidence to walk away.
Bottleneck diagnostic with prioritized, investment-ready recommendations
Working POC with quantified performance improvement and security validation
Business case and ROI projection
Execution plan with milestones, resourcing, and risk mitigation

Acceleration Pod

Mode 2

For portfolio companies where the bottleneck is already identified and the team is ready to execute. A senior-led practitioner pod embeds directly into the engineering organization, no discovery, no ramp-up.
Hands-on practitioners embedded inside the engineering team
SWAT-team oversight from the CAIO, AI Architect, and AI-focused TPO throughout execution
Sprint-based delivery with weekly progress reporting to the PE sponsor
Structured handoff that leaves the team stronger, not dependent
Investment: Rate-card-based engagement (time and materials) across LATAM, US, and EU resources.

Embedded AI Modernization Partner

Mode 3

For portfolio companies with leadership alignment and a mandate for structural change. Forte embeds senior expertise directly into the business and pairs it with a scalable execution engine that builds the internal capability needed to sustain value beyond the engagement.
Embedded senior lead acting as a fractional transformation partner (2–3 days per week)
SWAT-team oversight and a dedicated execution pod that scales up or down
Continuous measurement against portfolio-standard KPIs
Cross-portfolio knowledge sharing for PE sponsors with multiple AI initiatives

Technology execution for portfolio value creation

AI & intelligent automation

Deploy AI solutions that improve productivity, automate manual processes, enhance customer experiences, and create new sources of business value.

Data & analytics platforms

The data foundation AI needs. BI, customer analytics, operational dashboards, and the pipelines that feed every downstream model.

Custom software development

New revenue-generating products, platform modernization, and the engineering velocity that compounds over multiple sprints.

Cloud engineering & platforms

Cloud architectures designed for scalability, cost efficiency, and the kind of operational agility AI workloads demand.

Technology transformation & modernization

Legacy system upgrades, cloud migration, and technical-debt reduction tied to specific value-creation milestones.

Quality engineering

Reliability, security, and performance , including AI-assisted test generation that compresses scripting time by up to 75%.

Technology due diligence & advisory

Pre-investment technology assessments, post-close roadmaps, and ongoing strategic guidance aligned to the PE value-creation plan.

Private equity case studies

From AI Pilots to Operating Reality

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50% Savings in Infrastructure Costs for Interfirst Mortgage Company

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400% Faster: How OppFi and Forte Group Accelerated the Launch of a New Credit Platform

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FAQs

What types of private equity firms do you work with?

We focus on small and mid-market PE firms and their portfolio companies , sponsors who don't have a dedicated AI organization in-house but want their portfolio companies to ship production AI. Sectors include fintech, healthcare, SaaS, multi-site services, and B2B software.

Can you scale engineering teams quickly for portfolio companies?

2–3 weeks. That's our Diagnostic + Proof Sprint , a senior SWAT team, a working POC on real data, and a clear execution plan. It's deliberately sized to be a low-risk first move for a sponsor or a portfolio CEO.

How do you measure success in PE engagements?

Against portfolio KPIs the sponsor already tracks: engineering velocity (DORA metrics, cycle time, throughput), OpEx and unit-cost reduction, revenue-generating product milestones, and AI-specific measures like adoption, rework reduction, and cost-per-feature.

How do you handle the gap between assessment and execution?

There is no gap. The same senior practitioners who run the diagnostic stay involved through execution , the CAIO, AI Architect, and AI-focused TPO provide oversight as the delivery team scales underneath them. No handoff to a different team after the sales process closes.

What happens if a proof-of-concept doesn't validate?

That's exactly what a proof of concept is designed to do. If an initiative doesn't validate, the sponsor gains valuable insight before committing significant time and capital. Every engagement delivers clear findings and recommendations, helping leadership make informed decisions about where to invest next.

What's the smallest engagement you'll take?

2–3 weeks. That's our Diagnostic + Proof Sprint , a senior SWAT team, a working POC on real data, and a clear execution plan. It's deliberately sized to be a low-risk first move for a sponsor or a portfolio CEO.

Can you scale engineering teams quickly for portfolio companies?

Yes. Elastic squads from 2 to 100 engineers across 10 delivery hubs, near-shore and off-shore. Pods can deploy in 2–3 weeks with no recruitment overhead.

Do you provide technology due diligence?

Yes , pre-investment technology assessments, AI-readiness diagnostics, post-close 100-day plans, and ongoing strategic advisory aligned to the sponsor's value-creation plan.

Can you work across multiple portfolio companies for the same sponsor?

Yes. We support PE firms with portfolio-wide delivery, consistent operating model, shared KPI frameworks, cross-portfolio knowledge transfer, and a single point of accountability at the sponsor level.

How do you approach technology risk management?

We identify security vulnerabilities, strengthen compliance controls, implement monitoring and governance, and reduce operational risk across portfolio company technology environments.

Let's accelerate value creation across your portfolio

What our experts say

Nearly 20% of private equity portfolio companies have operationalized generative AI use cases and see concrete results in year two of AI's sprint across the technology landscape.

Strategic AI implementation partners help portfolio companies determine where AI delivers meaningful results and build organizational support for adoption, treating AI as a tool in service of strategy while tackling change management challenges head-on.
Alex Lukashevich
Chief AI Officer

What our experts say

Private equity firms sitting on $2.1 trillion dollars in dry powder face insurmountable pressure from limited partners for efficient capital allocation.

80% of private equity workflows rely heavily on technologies for deal sourcing, due diligence, and portfolio management. Expert development partners accelerate value creation initiatives while 95% of firms plan to multiply AI investments in the next 18 months.
Egor Goryachkin
CDO

What our experts say

Two-thirds of private equity clients implemented at least one AI initiative in their portfolio by 2024.

Specialized analytics partners enable enhanced data analysis - evaluating immense data volumes from financial reports, media, market data, and internal systems in real-time for more informed and faster investment decisions while general partners expect operational value creation to become more important than financial engineering in five years.
Lucas Hendrich
CTO

What our experts say

The biggest AI adoption challenges in private equity are conflicting internal expectations, skills gaps across portfolio companies, fragmented data ecosystems with legacy systems, and cybersecurity threats.

Strategic technology partners help firms scale AI enterprise-wide, utilizing knowledge and synergies from single portfolio companies and leveraging them across others while 78% use AI in at least one function yet only one-third scaled successfully.
Sergey Ilin
VP of AI