Product teams adding AI-native experiences
Create differentiated generation, assistance, conversation, transformation, and multimodal workflows inside an existing or new product.
Text, document, voice, image, code, and multimodal product capabilities
Generative AI development
Rokad develops generative AI applications and product features with model strategy, grounding, evaluation, controls, interfaces, and production operations.
Designed for / 01
A focused delivery model for the organisations that need it.
Generative AI becomes valuable when it is designed around a defined user task, evidence, quality standard, workflow, and operating cost. Rokad builds generation, transformation, extraction, conversation, voice, document, image, code, and multimodal capabilities within reliable software systems.
Organisations improving knowledge work
Support drafting, summarisation, extraction, review, translation, classification, and evidence-based analysis.
Teams moving beyond prompt prototypes
Introduce data, workflow, evaluation, security, cost, latency, fallback, and operational control.
Challenges / 02
The problems this service is built to solve.
Outputs are inconsistent or difficult to trust
The system lacks task definition, grounding, output structure, validation, examples, evaluation, and user feedback.
Model cost and latency undermine the product
Every request uses the same context and model without routing, caching, batching, limits, or economic controls.
Sensitive data crosses unclear boundaries
Provider, retention, logging, access, prompt injection, content, and output risks have not been designed explicitly.
Capabilities / 03
What Rokad can deliver.
01
Conversational, drafting, summarisation, extraction, and transformation applications
02
Document, voice, image, video, code, and multimodal workflows
03
Prompt, context, schema, tool, and structured-output engineering
04
Model selection, routing, fallback, caching, batching, and cost control
05
Grounding, retrieval, validation, moderation, and human review
06
Evaluation datasets, quality metrics, tracing, feedback, and release controls
07
Product interfaces, APIs, integrations, deployment, and managed operation
Solution components / 04
The system behind the visible product.
User workflow
The input, context, interaction, review, editing, approval, export, and downstream action around the generated result.
Generation pipeline
Model, instructions, examples, context, retrieval, tools, output schema, validation, retry, and fallback.
Safety and governance
Data access, provider controls, content policy, injection defence, moderation, review, logging, and retention.
Quality and economics
Evaluation, user feedback, latency, token usage, model routing, caching, cost allocation, and version comparison.
Use cases / 05
Where this capability creates practical leverage.
Document intelligence
Extract, classify, summarise, compare, draft, and route information from contracts, reports, forms, and records.
Product copilot
Help users understand data, complete tasks, generate work, and navigate application capabilities in context.
Voice and conversational application
Combine speech, language, tools, retrieval, memory, and escalation for a defined service or workflow.
Content production system
Generate, transform, localise, review, approve, and publish content under brand, evidence, and workflow controls.
Architecture and integration / 06
Designed to fit the wider technology environment.
Model portfolio
Route tasks across managed, open-weight, specialised, local, or fallback models based on quality, privacy, latency, and cost.
Context boundary
Assemble only the authorised, relevant, current evidence required for the task and defend the instruction hierarchy.
Structured result path
Use schemas, validation, deterministic rules, review, and downstream contracts where generated output affects systems or decisions.
Quality and control / 07
Production requirements are part of the build.
Measured behaviour
Representative evaluation data, quality criteria, failure modes, and release thresholds are defined before expanding production use.
Controlled actions
Permissions, policy checks, approval gates, audit trails, fallbacks, and escalation paths govern consequential AI behaviour.
Observable operation
Inputs, outputs, retrieval, tool calls, latency, cost, model versions, and quality trends are monitored appropriately.
Delivery / 08
A controlled path from requirement to operation.
Discover
Clarify the business outcome, users, workflows, constraints, dependencies, risks, and measurable acceptance criteria.
Architect
Define the system boundaries, data, integrations, security, operating model, delivery sequence, and technical decisions.
Build and validate
Deliver in controlled increments with stakeholder review, automated testing, documentation, and production-quality engineering.
Deploy and improve
Launch safely, establish observability and support, then improve the system using operational evidence and user feedback.
Typical deliverables
Generative AI use-case, data, risk, and model assessment
Workflow, context, model, evaluation, and control architecture
Production application, API, interface, and integrations
Prompts, schemas, retrieval, validation, moderation, and fallbacks
Evaluation datasets, quality thresholds, cost, and latency controls
Deployment, monitoring, governance, and operating documentation
Engagement models / 09
Use the delivery structure that matches the work.
Fixed-scope delivery
A defined outcome, scope, acceptance criteria, milestones, and commercial structure for a bounded project.
Dedicated product team
A stable cross-functional team delivering an evolving roadmap with shared product and engineering ownership.
Embedded specialists
Specialist engineers working inside an existing product, technology, data, design, or operations team.
Managed evolution
Ongoing reliability, security, maintenance, feature delivery, and roadmap execution after launch.
Related capabilities / 10
Continue through the wider product and technology system.
01
RAG and knowledge systems
Ground generation in governed documents and enterprise knowledge.
02
AI agents
Allow generated reasoning to coordinate approved tools and multi-step work.
03
AI integration
Embed generative capabilities into existing products and workflows.
01
Software development
Custom platforms, backends, integrations, operational systems, and software modernisation.
02
Web development
Web applications, websites, frontend systems, content platforms, and modernisation.
03
Managed technology services
Ongoing maintenance, cloud, security, reliability, support, and continuous engineering.
FAQ
Generative AI development
Scope, ownership, assumptions, delivery, security, and long-term operation are clarified before work begins.
01Which model provider should we use?
Which model provider should we use?
We compare quality, modality, context, latency, cost, privacy, regional availability, tooling, reliability, and portability. The system can route across more than one model where justified.
02Can generative AI produce structured data?
Can generative AI produce structured data?
Yes. We use constrained schemas, extraction patterns, validation, deterministic checks, confidence or review rules, and retries before downstream use.
03How do you reduce hallucinations?
How do you reduce hallucinations?
We narrow the task, ground outputs in authorised evidence, require citations where appropriate, use structured outputs, validate claims, add review, evaluate failures, and avoid using generation where deterministic logic is superior.
04Can sensitive data remain private?
Can sensitive data remain private?
Yes. The design can use provider privacy controls, regional services, private networking, open-weight models, self-hosting, access controls, minimisation, redaction, and explicit retention policies.
AI development
Turn generative capability into a controlled product or workflow.
Rokad can define the task, evidence, model strategy, quality thresholds, user experience, and production operations.
Contact / 05
Bring us the difficult technology problem.
Tell us what you need to build, improve, procure, deploy, or operate. We will respond with a practical next step.