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AI Development for Marketing

Woltrio builds the AI marketing software, we do not run your campaigns. Predictive lead scoring trained on your own CRM history, content pipelines with brand guardrails, personalization engines, attribution you can defend in a board meeting, and the martech plumbing that connects it all. We work with B2B SaaS, ecommerce and marketing teams across the US and UK on $5,000 to $150,000 engagements, building software you own rather than another subscription you rent.

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What We Build

Marketing software with AI where it earns its place, and ordinary reliable engineering everywhere else.

Scoring trained on your own closed-won and closed-lost history rather than a vendor's generic model, so sales works the accounts most likely to convert and the score explains why it ranked them.

How We Keep AI Marketing Honest

AI makes it trivial to produce more marketing. The engineering that matters is what stops that from becoming more noise, more risk and more numbers nobody trusts.

Brand voice and claim guardrails

Your style guide and prohibited claims are enforced as constraints in the pipeline, not as a prompt suggestion, with approval gates on anything customer-facing or regulated.

Grounded content, not invented content

Retrieval over your own product documentation, case studies and pricing so generated copy is traceable to a source, which is what keeps a confident-sounding false claim out of a campaign.

Measurement you can defend

Holdout groups and incrementality testing rather than last-click self-attribution, so you can tell the difference between a campaign that caused revenue and one that stood next to it.

First-party data, consent and privacy

GDPR and CCPA-aware handling, consent mode, data minimization and cookieless-ready measurement, built for a first-party world rather than retrofitted after the next deprecation.

Model evaluation and drift monitoring

Lead scores decay as your market shifts. We ship evaluation sets, monitoring and a retraining schedule, so a model that quietly stopped working gets caught by an alert rather than by a bad quarter.

The stack we build on

Python and TypeScript services against BigQuery or Snowflake with dbt, the Anthropic and OpenAI APIs, and the HubSpot, Salesforce, Klaviyo, Braze and Segment ecosystems.

Why a Boutique AI Marketing Partner

AI marketing tooling for small and mid-sized companies commonly runs $20,000 to $75,000, broader custom AI builds $50,000 to $500,000 and up, and a mid-market martech stack costs $120,000 to $350,000 a year once implementation and integration are counted honestly. Woltrio sits deliberately below the enterprise tier at $5,000 to $150,000. We are a software company, not a marketing agency and not a license reseller, so what you get is a system your team owns, integrated with the tools you already pay for. Budget a further 15 to 25 percent per year for retraining and maintenance.

B2B SaaS teams scoring, routing and enriching inbound leadsEcommerce brands personalizing lifecycle and retention messagingMarketing teams losing days a month to manual reportingAgencies productizing a repeatable service into softwareMartech startups building a first product or MVP

Our Development Process

  1. 01

    Defining Scope & Specification

    First, we define the project goals, target audience and user cases which helps us develop a Software Specification (SFS). Preparing an SRS ensures clear expectations and that everyone is on the same page before we start prototyping.

  2. 02

    Creating Prototype

    The second step involves developing an initial version of the app to visualize UI/UX and core functionalities. We then gather feedback, make adjustments and lock in on a prototype for development.

  3. 03

    Development Services

    It is time to choose the right tech stack and implement user-facing features with optimized performance. We ensure UI/UX feasibility, validate inputs and collaborate with other team members to achieve the best results.

  4. 04

    Quality Assurance & Testing

    Identifying and fixing bugs is crucial for customer satisfaction. We achieve this by deploying the solution in a test environment and repeating the process until the app is error free.

  5. 05

    Maintenance and Support

    Launching a product is not the end. We monitor its performance post-launch and fix issues proactively. Support services include applying regular updates and enhancements without compromising functionality.

Frequently
Asked Questions

Seeking basic information? Our FAQ section is a ready reckoner with precise answers to the most probable queries.

Are you a marketing agency or a software development company?

A software development company. We do not run campaigns, buy media or manage your ad accounts. We build the systems marketing teams and agencies use: lead scoring models, content pipelines, personalization engines, attribution reporting and the integrations underneath them. Clients typically keep their agency or in-house team for strategy and execution, and bring us in when the tooling they need does not exist off the shelf.

How much does custom AI marketing software cost?

AI marketing tooling for small and mid-sized companies commonly lands between $20,000 and $75,000, while broader custom AI projects run $50,000 to $500,000 and up. Woltrio works from $5,000 to $150,000 depending on scope: a single scoring model or reporting pipeline sits at the low end, a personalization engine with full martech integration at the high end. Budget 15 to 25 percent of build cost annually for retraining and maintenance.

Does AI-generated content hurt SEO rankings?

Not by itself. Search engines reward helpful, original, demonstrably useful content and penalize thin, unoriginal content at scale, regardless of whether a human or a model produced it. The failure mode is not AI, it is publishing volume with nothing new in it. That is why we build content pipelines grounded in your own product knowledge and data, with human review before publishing, rather than an unattended generator pointed at your CMS.

How accurate is AI predictive lead scoring?

Accuracy depends almost entirely on the quality and volume of your historical CRM data. A model trained on a few thousand of your own closed-won and closed-lost records will meaningfully outperform generic vendor scoring, because it learns your actual buying patterns. With sparse or badly maintained CRM data, the honest answer is that data cleanup comes first, and we will say so before taking the project.

Should we build custom AI or use the AI built into HubSpot or Klaviyo?

Use the built-in features first. Platform AI covers send-time optimization, basic scoring, subject lines and standard segmentation perfectly well, and it is already paid for. Build custom when the logic is specific to your business model, when you need to combine data the platform cannot see, when scoring must explain itself for sales to trust it, or when per-contact pricing makes the platform route expensive at your volume.

How do you measure whether AI marketing actually worked?

With holdout groups and incrementality testing. Platform-reported conversions are self-attributed and systematically flattering, so the only reliable method is withholding treatment from a comparable group and measuring the difference. We build this into the system from the start, because retrofitting a control group after launch means the first quarter of results can never be properly evaluated.

Is AI marketing personalization compliant with GDPR?

It can be, and it depends on lawful basis rather than on the technology. Personalization built on first-party data with clear consent, purpose limitation, data minimization and a genuine opt-out is compliant. What creates risk is profiling without consent, opaque automated decisions that materially affect people, and sending personal data to third-party models without a processing agreement. We design for the first case and engineer against the second.

AI Development for Marketing.

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Powering Your Solutions With

Python
Selenium
React Native
HL7 FHIR
Flutter
TypeScript
Flutter
Python
Selenium
React Native
HL7 FHIR
TypeScript
Python
Selenium
React Native
HL7 FHIR
Flutter
TypeScript
Flutter
Python
Selenium
React Native
HL7 FHIR
TypeScript