AI Engineering Services for Software Vendors | Rakam AI

Your team knows how to code. We know how to ship AI.

We integrate with your team to identify the right use cases, build them, and put them in production.

Without a specialized AI partner 6-12 months
With Rakam 4-8 weeks
1

AI Product Strategy

We help you identify and build the right AI features.

Most software vendors know they need AI. Few know which features will actually increase their users' productivity. We work with your team to study your users' needs, prioritize by ROI, and build a roadmap that turns AI from a cost center into a lasting competitive advantage.

This is not about integrating AI for the sake of it. It is about finding the features your competitors cannot replicate — and getting there before they do. It is a matter of survival.

User needs study

Understand what your users actually need from AI — not what is trendy.

Feature prioritization

Score each AI feature by potential ROI, complexity, and market differentiation.

AI Product Roadmap

A sequenced plan that maximizes impact quarter after quarter.

Quarterly reviews

Continuous roadmap refinement based on market shifts and client feedback.

2

Full-Stack AI Engineering · Open Source ↗

The complete AI production pipeline, x10 faster together.

This is what we do every day for over 15 software vendors. We work alongside your team at every step of the pipeline — bringing the AI expertise, frameworks, and velocity so your engineers can focus on what they do best. Together, we turn your roadmap into production systems at a pace you could not reach alone. Strategy + Velocity + Compliance.

01

Ideation

Identify user needs, study the market, spot the AI use cases that will generate the most impact. We work with your product team to separate hype from value.

02

Evaluation

Create evaluation datasets and benchmarks before writing production code. We measure what success looks like so we can prove it later.

03

AI Engineering

Build production-grade AI systems: RAGs, Agents, Matching Engines, Data Pipelines, Computer Vision. We handle the research, the architecture, and the hard engineering.

04

Backend Integration

Develop APIs, MCP servers, and backend services that plug into your existing stack. Your auth, your data, your infrastructure.

05

Deployment

Containerized delivery on your cloud (OVH, AWS, GCP) or on-premise. CI/CD pipelines, staging environments, production rollout.

06

Monitoring

MLflow observability, evaluation traces, latency tracking, quality metrics, drift detection. We don't just ship — we watch it work.

Your team would take 6-12 months. With Rakam, 4-8 weeks.

Systems we build

RAG Systems
AI Agents
Matching Engines
Computer Vision
Data Pipelines
Chatbots
Evaluation SDKs
MCP Servers
3

"We can do it ourselves"

We don't replace your team.
We make them 10x faster.

Rakam is symbiotic with your engineering team. We take on the heavy AI engineering tasks — research, system design, evaluation frameworks, production infrastructure — so your team can focus on product integration and domain expertise.

And most importantly: we train your teams. Every project includes knowledge transfer. Your engineers become more autonomous with AI over time. The goal is not to create a dependency — it is to make you capable.

Knowledge transfer built into every project
Your team owns the code and the infrastructure
Progressive training on our frameworks and tools
Growing autonomy quarter after quarter

"At Beetween, we have a very competent technical team. Yet, we wanted to go faster, beat the competition and take an AI leadership role in the HRTech sector. Rakam worked hand in hand with our team, took on heavy AI engineering tasks, and helped our team be more autonomous in producing AI. By working with Rakam, your own team goes much faster, and the overall operational system is much more efficient."

Philippe Dulong De Rosnay

Philippe Dulong De Rosnay, CEO of Beetween

HRTech. Applicant Tracking System

4

Maintenance & Evolution

AI in production is a living thing. We evolve your systems with you.

An AI system does not stop at deployment. Models drift, data changes, users discover new needs. We ensure production monitoring and continuously evolve your systems.

No black box. You have full visibility into the quality, costs, and performance of every AI system in production.

Continuous monitoring

MLflow observability, quality metrics, latency tracking, drift detection. We watch that it works.

Iterative improvements

Prompt tuning, data enrichment, performance optimization — based on real user feedback.

Capability evolution

Adding new tools, new data sources, new use cases. Your AI system grows with your product.

Continuous compliance

AI Act compliance tracking, regular audits, guardrails and traceability updates.

How we work with you

Two engagement models adapted to your AI maturity.

Initial Project

4-8 weeks - Fixed scope

One-off AI Systems

A production-ready AI system tailored to your specific use case, delivered in weeks. We handle the full pipeline from evaluation to deployment, with optional knowledge transfer to your team.

Fixed scope, fixed price
The fastest way to test a high-ROI AI feature
Knowledge transfer included
Ideal before committing to a full AI program
Discuss a project
Most popular

Subscription

3-5 systems/year - Ongoing

AI Leadership Program

Continuous AI product development at industrial scale. We embed with your team to deliver 3 to 5 AI systems per year following a rigorous roadmap we build together. This is how you become the AI leader in your market.

Quarterly customer research + feature prioritization
Ongoing engineering capacity embedded in your team
Strategic product consulting included
Industrial production of your AI roadmap
Discuss a project

[Frequently asked questions]

We start every engagement with a strategic assessment that calculates the potential ROI before writing a single line of code. If the numbers do not add up, we will tell you. On average, our clients see their first AI feature increase their users' productivity within 3 months. The question is not whether AI will generate ROI — it is whether you will capture it before your competitors do.

Your tech team excels at building your product. AI engineering is a different discipline — it requires specialized research, evaluation frameworks, and production patterns that take years to master. We do not replace your team. We accelerate them. Most of our clients have strong internal teams (see Beetween). They chose us to go faster and avoid costly mistakes.

We build AI systems that plug into your existing stack via APIs and MCP servers. We deploy on your cloud (or on-premise), use your authentication, and follow your CI/CD processes. Our systems are containerized and sovereign — they run where you need them, with no vendor lock-in.

All Rakam systems are AI Act compliant by design. We include our proprietary SafeBox technology for bias removal and anonymization. We work with local model providers for sovereignty, and every system includes data obfuscation when handling personal data. Our CEO published an analysis of the AI Act's implications in Polytechnique Insights.

That is actually our goal. Every project includes knowledge transfer. Our subscription model is designed to make your team progressively more autonomous. You own the code, you own the infrastructure, and we train your team to maintain and evolve the systems we build together.

Move from hype to real impact

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