Medra
Book a demo
Medra vs. Building in-house

Building it in-house is the most expensive way to arrive late.

Your team can wire an LLM to WhatsApp in an afternoon. The hard part is everything else: integrations, voice, memory, security, escalation, metrics and, above all, getting the organization to actually use it. That is where most AI projects die.

Talk to the people who would build it See the data
Head to headIn-houseMedra
Time to production9 to 12 moWeeks
Specialists you must hire9 roles0
Enterprise deployments behind the team040+
Change managementYour problemIncluded
~10 mohead start you keep by not building it yourself. Reference timelines, scope varies.
Weeks, not quartersExpert team from day oneChange management includedSOC 2 Type II19+ countriesEvery languageAdversarial stress testing
The gen AI paradox
80%

Nearly 8 in 10 companies already use generative AI. More than 80% of those same companies report no material impact on earnings.

McKinsey & Company, “Seizing the agentic AI advantage”, 2025.

Each dot is a company. The green ones see results. Which side will your project land on?

01

Horizontal tools

Copilots and chatbots rolled out everywhere, with an impact so diffuse nobody can measure it.

02

Pilots that never scale

Proofs of concept stuck in the lab, never wired into the real commercial process.

03

No infrastructure, no leadership

Missing the architecture, the team and the change management to turn an experiment into an operation.

The problem is almost never the model. It is everything around the model. That is exactly what Medra takes off your plate.

What never makes it into the plan

“It’s just a prompt connected to WhatsApp.” That’s the tip. The other 90% is underwater.

LLM + APICRM and ERP integrationsWhatsApp API and templatesVoice, latency and voice notesMemory and context per customerStress testing against attacksHuman escalation with contextClassification, metrics, reportingSecurity and SOC 2 complianceCultural change management

Each of these layers is a project of its own. In-house, you discover them one by one, in production, in front of your customers. At Medra we have solved them dozens of times.

  • What the roadmap showsA prompt and one integration
  • What operations demand8 technical layers and 1 organizational
  • Who fixes it at 3 a.m.In-house: someone on your team. With Medra: us.
  • Who improves it every weekIn-house: when there is time. With Medra: it is our job.
Time to production

While your team is still hiring, Medra is already talking to your customers.

Building in-houseTypical scenario
Hire the team
Architecture
Integrations and prompts
Pilot
Production?
With MedraTeam already in place
Live, optimizing against your KPI every week
Diagnosis · weeks 1 to 2Custom agent build · weeks 2 to 6Stress testing · weeks 6 to 8In production
~10 monthsof commercial advantage you keep

Reference timelines. They vary with each project’s scope and integrations.

The team

This is not an AI project. It is an entire team you would have to hire, train and keep.

If you build it in-house

You need to find, in a market that fights over them:

AI architectBackend engineersPrompt engineersVoice engineerQA and securityData analystsProduct managerCommercial process expertChange management lead
And hope nobody quits halfway.Months of hiring
With Medra

We assign an expert team from day one:

Agent architectsSpecialized prompt engineersData analystsAccount managers from Uber and Mercado LibreAI team backed by academiaAdoption specialists
Commercial and AI experts at the same table.Day 1

Our AI team works alongside Universidad de Buenos Aires, NJIT, the Centro Interinstitucional en Ciencia de Datos and the Laboratorio de Inteligencia Artificial Aplicada.

Change management

AI doesn’t fail in the code. It fails in the culture. So we don’t hand you software. We lead the change with you.

01

Process diagnosis

We learn how your team sells, collects and supports today. We build for your process, never on a template.

02

Co-design with your team

Your leaders set the tone, the limits and the goals. The agent talks like your best people.

03

Adoption and training

We prepare your teams to work with the agent, not against it. Nobody is left behind.

04

Humans where they matter

Complex cases reach your specialist via Slack, email or in-app notification, with a summary and a classification. No context to rebuild.

The invisible cost

The development budget is not the expensive part. The months without results are.

Cost of arriving late
USD 640,000

Revenue, recoveries or savings your company fails to capture while the in-house project is still not live. Before salaries, infrastructure, or the risk that it never ships.

Expensive myths

What gets said in the meeting. And what happens next.

Side by side

Point by point.

CriteriaBuilding in-houseMedra
Time to productionQuarters, if everWeeks
Specialized teamTo be hired and retainedAssigned from day one
Accumulated experienceYour first project40+ enterprise projects in 19+ countries
Commercial know-howDepends on who you hireTrack record at Uber, Mercado Libre and other large companies
ChannelsOne, if you’re luckyWhatsApp, calls, email, SMS, Instagram, web and Slack
SecurityAudit from scratchSOC 2 Type II certified
Adversarial stress testingYour customers find the bugsAutomated sandbox tests before launch
Change managementOut of scopePart of the service
Continuous improvementWhen there is timeWeekly optimization against your KPI
Risk100% yoursShared with a partner that lives off your results

Your competitive advantage is not knowing how to build agents. It is knowing your customers. Leave us the part that doesn’t set you apart.

Join the 20% that actually sees results.

30 minutes with the people who would build your agent. Bring one process you want to fix.

Book a demo See Medra vs. generic chatbot