Consulting, development and talent to accelerate with AI.
We integrate strategy, execution and operations in six services that cover the full cycle: from diagnosis to deployment, from pilot to scale. We don't subcontract.
Custom development
We design and build enterprise platforms with AI layers that reach production in weeks, not months.
Request this serviceDESIGN
Domain architecture, API specs and data models. What the system needs before writing code.
DEVELOPMENT
Microservices, LLM reasoning and security. 2-week sprints with visible deliverables.
INTEGRATIONS
We connect to your existing policy core, rating, CRM, contact center, KYC/AML and DWH/Lakehouse.
OPERATIONS
DevSecOps, encryption, SLOs/alerts, and auditability from launch.
What we hear before we start working together.
"We hired a dev shop, and they delivered what we asked for, not what we needed."
The initial brief is always incomplete. Requirements change once the business sees them working. A firm that only executes specifications delivers correct software that solves the wrong problem. Our model includes the definition stage as part of the engagement, not as an add-on.
"They delivered the system and disappeared."
Launch isn't the finish line, it's where the real problems start. Bugs in production, users who don't adopt, edge cases nobody specced. Post-launch support isn't an optional service; it's part of what makes a project actually succeed.
Five phases, the same team from start to finish.
PROBLEM DEFINITION
Before writing a single line of code, we understand the problem. Workshops with business and technical stakeholders, mapping of current processes, identification of regulatory and technical constraints, and definition of measurable success criteria. The output is a functional design document, not a generic requirements spec.
DESIGN & ARCHITECTURE WITH DOMAIN-DRIVEN DESIGN
We apply Domain-Driven Design as our core architecture methodology: we model the software around the business domain, not the other way around. In practice, this means that before defining tables, APIs or microservices, we build the shared language between the business and the technical team. At an insurer, that means explicitly modeling concepts like policy, endorsement, claim, premium or insured risk, with their rules, limits and relationships, the same way the underwriting team understands them. The result is software the business can read, the team can maintain, and that scales without accumulating invisible technical debt.
ITERATIVE DEVELOPMENT
Short sprints with visible deliverables. The client sees real progress, not status reports. We use orbit mindcode as our development environment, which translates into more consistent, better-documented code with less technical debt from day one. The domain model defined in the previous phase guides every technical decision during development.
LAUNCH & STABILIZATION
Support during deployment, user training and active support during the first weeks in production: the period when most problems surface and when having the team available matters most.
SUPPORT & EVOLUTION
Corrective maintenance, incremental improvements and the capacity to scale the product as the business grows. Because the system was built on an explicit domain model, any developer who joins the project can understand the business logic by reading the code, not by hunting down whoever wrote it.
Custom software design and development with end-to-end support: from defining the challenge to implementation and post-launch support. We don't just execute requirements, we co-design solutions. The client doesn't need to know exactly what to build; they need to be clear on which problem they want to solve.
Why rocket code, not a conventional dev shop.
- ✕ Entry point. Functional requirements
- ✕ Architecture. Technical decisions with no domain model
- ✕ Business knowledge. Long learning curve
- ✕ AI in the product. An add-on at the end, if the client asks
- ✕ Final deliverable. A system in production
- ✕ Post-launch. Support under a separate contract
- ✕ Internal tooling. Standard market stack
- ✓ Entry point. Problem definition
- ✓ Architecture. Domain-Driven Design: the business dictates the structure
- ✓ Business knowledge. Financial DNA: insurance, banking, investments
- ✓ AI in the product. Built in from the architecture design stage
- ✓ Final deliverable. A system + a documented domain model + a trained team
- ✓ Post-launch. Part of the engagement from day one
- ✓ Internal tooling. orbit mindcode: less technical debt, more speed
What we've already built, by industry.
The kind of system this service produces: thirty real examples across three industries, from regulatory OCR to a full digital wallet.
- 01AI underwriting for facultative risks
- 02Major medical claims management
- 03Fraud detection in issuance and claims
- 04Core insurance system for life lines
- 05KYC case files under LISF Article 492
- 06Data extraction from scanned policies and endorsements
- 07Simultaneous quoting across insurers
- 08Remote claims adjustment with guided evidence
- 09Vehicle catalog harmonization
- 10Reinsurance slip comparison
- 01End-to-end credit origination
- 02Digital client onboarding with KYC
- 03Transaction monitoring for AML
- 04Automatic payment reconciliation against the core
- 05Collections applied to issued receipts
- 06Real-time multi-bank position and liquidity
- 07Reinsurance email management with AI agents
- 08Secure interoperability with the Single Identity Platform
- 09Contracts with certified electronic signature
- 10Altered-document detection in origination
- 01End-to-end digital wallet
- 02Investor onboarding and KYC
- 03Online foreign-exchange trading
- 0424/7 trading and reporting for end clients
- 05Brokerage back-office automation
- 06Funding and disbursement with full traceability
- 07Account statements and regulatory reporting
- 08Real-time position and balance consolidation
- 09Operations monitoring and alerts
- 10Portals for funds and brokerage firms
AI Consulting
Comprehensive evaluation of your enterprise AI maturity and design of a roadmap with quick wins and long-term vision.
Request this serviceDIAGNOSIS
Audit of processes, data, current stack and organizational capacity. We identify where AI moves the needle.
USE CASES
We list and prioritize cases by measurable ROI. We eliminate those that sound good but don't pay off.
ROADMAP
12–24 month plan with 60–90 day quick wins + long-term strategic capabilities.
GOVERNANCE
Operating model, AI committee, success metrics and change management plan.
What we do in every engagement.
AI maturity diagnosis
We assess data, infrastructure, processes, talent and organizational culture. We use a proprietary framework calibrated for regulated financial operations supervised by CNBV, CNSF and CONDUSEF, where traceability, risk control and compliance aren't optional.
Identifying prioritized use cases
We don't hand over a list of 40 opportunities. We select the 5-8 cases with the highest real impact potential, weighing implementation time, data availability and the organization's appetite for change.
Roadmap design
Quick wins executable in 60-90 days plus structural initiatives spanning 12-24 months. Every initiative comes with an effort estimate, expected KPIs and technical dependencies.
Implementation support
We don't just hand over the map. We can execute it.
A comprehensive assessment of your enterprise's AI maturity and a transformation roadmap with quick wins and long-term vision. The result isn't a generic trend report: it's an honest diagnosis of where your organization stands today, what you can solve in 90 days, and what you build in 18 months: with use cases prioritized by operational impact, technical feasibility, and measurable return.
Why rocket code, not a generalist consultancy.
- ✕ Industry knowledge. Generic frameworks
- ✕ Deliverable. An opportunities report
- ✕ Continuity. Closes the door once delivered
- ✕ Regulation. A general framework
- ✕ Speed. 3-6 months of diagnosis
- ✓ Industry knowledge. Financial DNA: insurance, banking, investments
- ✓ Deliverable. An executable roadmap with prioritized cases
- ✓ Continuity. Can implement what it diagnoses
- ✓ Regulation. CNSF, CNBV, CONDUSEF, LISF built in
- ✓ Speed. Quick wins in 60-90 days
What the consulting looks like in each pillar.
Insurance
Insurers
Mass-underwriting automation diagnosis: identifying which lines are candidates for automatic rating, which claims-history data is structured, and how to cut issuance time from days to minutes.
Brokers
Portfolio management maturity assessment: how to automate renewal tracking, expiration alerts and account prioritization by lapse risk, without replacing the broker's commercial relationship.
MGAs
Dynamic pricing capability assessment: which weather, geospatial, or sector-specific variables can be integrated into the rating model, and over what timeframe.
Banking
Banks
Back-office automation diagnosis: credit document processing, identity validation KYC, transaction anomaly detection. Identifying what's already in production versus what's underused.
Fintechs
Personalization maturity assessment: how to use transactional behavior data to build differentiated product experiences, from savings recommendations to proactive risk alerts.
Savings banks
A transformation roadmap built around real constraints: smaller tech budgets, small teams, legacy databases. The diagnosis identifies what can be solved with existing tools before investing in new infrastructure.
Investments
Investment funds
Portfolio data intelligence diagnosis: automating performance reports, benchmark-deviation alerts and real-time risk monitoring. Identifying what analysis is done manually today and how much team time it consumes.
Brokerage firms
Client service capability assessment: how to automate balance inquiries, positions, and returns for retail clients without degrading the experience for institutional accounts that require a personalized relationship.
AI agent development
Agents built to fit your operation, not a generic platform: we design, train, and deploy each agent on your processes, your rules, and your business knowledge.
Request this serviceCUSTOM-BUILT AGENTS
Sales, underwriting, support, collections: each agent is designed from scratch for your process, with its own prompt, model, and memory.
ORCHESTRATION
Visual flows combining AI agents + humans at critical points. No code required.
HUMAN-IN-THE-LOOP
We define where a human validates without stopping the flow. AI proposes, the expert approves.
CONTINUOUS TRAINING
Integrated feedback loop. Each conversation tunes the model. Per-agent metrics.
We don't sell a generic platform: we develop custom agents. Ten years inside insurance, banking, and investments gave us the knowledge to design, train, and deploy agents tailored to each client's exact need, across four capabilities: document extraction, operational automation, service and interaction, and decision intelligence. The orchestration is ours; the processes, rules, and knowledge each agent is trained on are yours.
The four types of agents we build.
Document Extraction & Intelligence Agents
Agents specialized in reading, interpreting and structuring information contained in non-standardized documents. They operate on PDFs, emails, forms and external portals.
Use cases for insurance
- Policy data extraction: terms, coverages, validity periods, and premiums
- Collections document extraction
- Issuance information extraction from agent portals
- Underwriting documentation analysis: endorsements and renewals
- KYC/AML file processing
Related products
Operational Agents
Agents that execute complete workflows autonomously, making intermediate decisions without human intervention at every step. Unlike a reactive chatbot, these agents are proactive: they access databases, send emails, update systems and chain actions toward a business objective.
Use cases
- Automatic classification and routing of incoming emails
- Validation and management of regulatory files
- Orchestration of quoting flows for vehicle fleets
- Automation of policy issuance and renewal processes
- Collections management and payment follow-up
Related products
Customer & Service Agents
Agents that interact directly with internal or external users, answering queries, escalating complex cases to humans and generating context-aware responses. The current model combines human and agentic capabilities: agents handle first contact and frequent questions, while human teams focus on complex cases.
Use cases
- Support for agents and brokers on policy status and procedures
- Internal assistants for underwriting and finance teams
- First-level claims inquiry management
- Smart notifications and proactive follow-up
Decision Support Agents
They assist decision-makers by gathering and analyzing relevant information, identifying options, evaluating potential outcomes and issuing recommendations.
Use cases
- Anomaly detection in claims: possible fraud
- Risk scoring and prioritization in underwriting
- Coverage recommendations based on client profile
- Real-time portfolio profitability analysis
Autonomous operations
On-demand enterprise AI capabilities. Proprietary methodologies with agnostic, agile, integrable and scalable logic.
Request this serviceON-DEMAND CAPABILITIES
Activate what you need: classification, RAG, scoring, voice, or vision. Scale by usage.
VENDOR-AGNOSTIC
Switch between OpenAI, Anthropic, AWS Bedrock or in-house models without rewriting anything.
INTEGRABLE WITH YOUR STACK
API-first, events, webhooks. Fits in what you have: we don't ask you to migrate.
SCALABLE WITHOUT OVER-ENGINEERING
Cloud architecture that grows with your volume without doubling your infra team.
Proprietary methodologies and technologies to build on-demand enterprise AI capabilities, always agnostic, agile, integrable and scalable. The client doesn't adopt a generic automation platform: they get an operation designed specifically for their business, with agents that understand their processes, rules, and regulatory constraints, and that scale up or down according to real demand.
Automating tasks isn't the same as operating a full process.
Traditional automation solves isolated tasks. An RPA that fills out a form. A script that moves a file. Useful, fragile, limited.
Autonomous Operations works on a different logic: instead of automating steps inside a human process, we design the entire process around agents that execute it end to end, with human checkpoints where the business needs them, not where the technology forces them.
The critical distinction is the supervision model. This isn't automation without control, it's supervised autonomy: agents operate, decide and execute within defined parameters; humans step in for exceptions, high-risk cases or decisions that require judgment AI doesn't yet have. That boundary is designed with the client, never assumed.
The most ambitious case: operations as a service.
The horizon for this service is the possibility of rocket code operating entire functions of the client's business through agents. Not as people outsourcing: as intelligent operating infrastructure.
Picture an insurer or MGA launching a 100% digital product without building a 40-person operations team. rocket code's agent layer executes five functions:
SALES
The agent guides the prospect, quotes in real time, handles objections, validates eligibility and closes the policy.
ISSUANCE
The agent generates the policy, validates the data against the core, issues the documents and delivers them to the insured.
COLLECTIONS
The agent monitors payments, sends reminders, manages reinstatements and escalates delinquent cases to the human team.
SERVICE
The agent resolves coverage questions, generates certificates, updates data and opens claims, handing off to a human when complexity warrants it.
CLAIMS
The agent receives the notification, requests documentation, validates coverage, assigns an adjuster and follows up, with full traceability.
The client's human team doesn't disappear, it focuses on what actually has value: complex decisions, strategic account relationships, product design, and oversight of agent performance.
Digital marketing LLMO
Highly technical strategy and execution. AI agents that automate commercial processes and optimize complex campaigns.
Request this servicePERFORMANCE
Paid campaigns with AI optimization, multi-touch attribution and actionable reporting.
SEO + CONTENT
Content strategy and technical SEO for organic capture with buying intent.
AI COMMERCIAL AGENTS
Conversational nurturing, qualification and AI-assisted closing on WhatsApp and web.
ANALYTICS + PR
Live dashboards, attribution and tech PR with specialized coverage.
Strategy and execution of highly technical digital marketing. We specialize in two capabilities that today operate separately in most organizations and that together define who wins the digital channel over the next five years: visibility in AI models LLMO and commercial execution automation through agents.
The battle for the digital customer is no longer fought only on Google.
For a decade, the battle for the digital customer was fought on Google. That channel is being disintermediated. A growing share of purchase decisions on financial products now starts with a query to an AI model: ChatGPT, Perplexity, Gemini, Claude.
The user doesn't sift through ten results to compare: they get one answer. And in that answer, some brands appear and others simply don't exist. The difference isn't set by ad budget, it's set by how the content is structured, and by the brand's authority and digital presence in the sources models use to build their answers.
How we work visibility and conversion.
LLMO: Visibility in Language Models
The equivalent of SEO for the generative AI era. It's not about ranking on page one of Google, it's about being part of the answer a model builds when someone asks about your category.
- LLM presence audit. We assess how the leading AI models mention you today.
- Content architecture for AI. We design the brand's content architecture to be a trustworthy, citable source for models.
- Digital authority building. Technical depth, brand consistency, sector-authority backlinks.
- Continuous monitoring and optimization. We measure brand presence in LLMs periodically and adjust strategy.
Commercial Agents: Execution Automation
Visibility attracts the prospect. Agents convert and retain.
- Qualification and nurturing agents
- Follow-up and reactivation agents
- Complex campaign automation
- AI-powered performance analytics
Staffing
Complete operational cells and specialized talent in AI, data, dev, and product for strategic accounts. Continuity, quality and know-how.
Request this serviceCOMPLETE CELLS
Multidisciplinary squad embedded in your operation: tech lead, devs, QA, product, AI.
SPECIALIZED TALENT
Access to +190 engineers who are financial sector experts. No fighting for talent in the market.
CONTINUITY
Client knowledge that survives turnover. Living documentation and formal handover.
PRODUCTIVITY SLA
Committed velocity and deliverables. Transparent monthly metrics with your team.
Provision of complete operational cells and specialized talent in AI, data, development and product for strategic accounts. The model guarantees continuity, delivery quality and accumulated know-how, without the client carrying the overhead of recruitment, payroll management or retention.
What rocket code delivers.
Cells, not individuals
We embed small, cohesive teams, not isolated profiles. A typical cell combines a tech lead, a data/AI engineer, and a product or QA profile, depending on scope. They work with rocket code's methodology from day one.
Talent with financial DNA
Our profiles come from real projects at insurers, banks, fintechs, and investment funds. They know the logic of a policy, understand an underwriting process, and know what CNSF or CNBV compliance means. There's no business learning curve.
Three ways to work with us.
Cell per strategic account
A team dedicated full-time to a specific client. Ideal for accounts with a 12+ month transformation roadmap or multiple parallel initiatives. The client has direct interaction with the cell, but rocket code keeps the management, methodology, and continuity.
Project-based reinforcement
Specialized profiles temporarily integrated into the client's internal team for a scoped project: implementing a model, migrating data, launching an agent. With a clear start date and deliverables.
Capacity expansion
For demand spikes or initiatives that don't justify a permanent hire. The client scales its operational capacity without long-term commitments or HR processes.
How we collaborate with you.
We don't start programming on Monday. We start by understanding. Each phase has visible deliverables, an owner on your side and one on ours.
Diagnosis
2–4 weeks. Processes, data, stack and use cases prioritized by ROI.
Design
Architecture, APIs, data models, AI governance and organizational change plan.
Implementation
2-week sprints with visible deliverables. Your team in the loop from day one.
Operations
ModelOps + LLMOps, SLOs, auditing and iteration. You keep the system, not the dependency.
Agnostic by design.
We have no stack religion. We choose based on your infrastructure, team and target cost, and switch when the context demands it.
We are the partner who understands your industry and speaks your language: technical, regulatory and commercial.
Which of the 6 services do you need first?
30 minutes with an expert. We respond with a concrete proposal in 48 hours. No sales agenda.