Turn fragmented workflows into measurable AI systems.
Litewave helps B2B teams connect their data, automate expensive manual work, and deploy AI in production — with clear scope, acceptance criteria, and measurable outcomes.
Workflow architecture
Illustrative system design
Data sources
Step 01APIs · Documents · CRM
AI workflow
Step 02Retrieve · Process · Validate
Measurable output
Step 03Results · Logs · Evaluation
Failure handling
Quality & cost
Built for B2B SaaS and software-enabled service teams with real customers, existing workflows, and technical staff.
The problem
AI pilots stall when the data and workflow don’t connect.
Useful AI depends on more than a model. It needs dependable inputs, integration with existing tools, clear boundaries, and a way to measure whether the work is actually improving.
Fragmented data
Your customer, operational, and product data lives across disconnected tools that do not share context.
Connect systems into a reliable source of information.
Manual bottlenecks
Teams spend valuable hours copying information, reviewing documents, and repeating predictable tasks.
Automate repetitive work without losing human oversight.
Pilot-to-production gap
A promising AI demo is not enough when real users need permissions, monitoring, reliability, and support.
Move from experimentation to maintainable software.
Services
Start with one expensive workflow. Expand only after proof.
Every engagement starts with a defined problem, a practical scope, and an agreed way to evaluate success. Build only what the workflow needs.
Workflow Opportunity Assessment
Understand one expensive workflow before committing to a larger implementation.
$2k–$5k
- Map the current process
- Estimate operational costs
- Review data and integrations
- Define scope and success criteria
Typically 1–2 weeks
Discuss this serviceAI Integration Sprint
Core serviceImplement one clearly defined AI use case within your existing business systems.
$15k–$30k
- Support triage and draft responses
- Document extraction and classification
- Internal knowledge with citations
- Evaluation and failure handling
Scope-dependent
Discuss this serviceData Infrastructure
Make fragmented business data reliable, accessible, and ready for downstream AI workflows.
Custom scope
- API and database integration
- Data cleaning and transformation
- Reliable ingestion pipelines
- Validation and access controls
Based on system complexity
Discuss this serviceProduction Deployment
Turn a validated solution into a production system your team can operate confidently.
$35k–$75k+
- Production integrations
- Permissions and security controls
- Monitoring and evaluation
- Documentation and handover
Scope and risk dependent
Discuss this serviceOngoing Operations
Keep deployed systems observable, dependable, and aligned with changing business needs.
$2k–$6k/mo
- Monitoring and incident handling
- Quality and cost evaluations
- Performance optimisation
- Agreed monthly improvements
Monthly engagement
Discuss this serviceFinal scope and pricing depend on systems, data access, security requirements, and delivery risk. Listed ranges are indicative, not binding quotes.
Our process
A clear path from problem to production.
No open-ended transformation programme. Each phase has a purpose, a deliverable, and a decision about what happens next.
Assess
Map one costly workflow, identify constraints, inspect available data, and define measurable acceptance criteria.
A scoped implementation plan
Integrate
Connect the required systems and build the smallest useful solution around your real operating process.
A working, testable solution
Deploy
Test failure cases, establish permissions, instrument performance, and prepare your team for production use.
A documented production handover
Operate
Monitor agreed quality and cost measures, resolve issues, and improve the system based on observed results.
An agreed operating plan
Progress should be visible at every stage.
Milestones, acceptance criteria, risks, and ownership are agreed before implementation begins.
Example use cases
Practical applications. Outcomes that can be evaluated.
These are illustrative engagement patterns, not claimed client projects or verified case studies. Actual results depend on the workflow, data, and implementation.
Support-ticket triage
Problem
Support teams manually categorise incoming requests and prepare repetitive responses.
Approach
Classify tickets, retrieve relevant context, and draft responses for human review.
Target outcome
Target faster handling, more consistent routing, and less repetitive work.
Document extraction
Problem
Important fields are trapped in PDFs, forms, and inconsistent documents.
Approach
Extract structured fields, validate results, and route uncertain cases for review.
Target outcome
Target less manual data entry and a clearer exception-review process.
Internal knowledge assistant
Problem
Employees struggle to find reliable answers across internal documents and systems.
Approach
Index approved sources, retrieve relevant passages, and generate answers with citations.
Target outcome
Target faster information retrieval with traceable source material.
What we measure
Depending on the use case, evaluation can include handling time, exception rates, extraction accuracy, answer groundedness, human review requirements, system reliability, and cost per completed task. Baselines and targets are agreed with the client rather than invented in advance.
Engagement model
Clear starting points. Scope before commitment.
Choose the level of help that matches your current stage. Larger implementations are scoped after technical discovery, not sold as a one-size-fits-all package.
$2k–$5k
For teams that need clarity before committing to implementation.
- One workflow mapped
- Data and integration review
- Cost and feasibility assessment
- Written scope and success criteria
$15k–$30k
For teams ready to solve one defined operational problem.
- One bounded use case
- Agreed integrations
- Testing and evaluation
- Documented handover
$2k–$6k/mo
For teams that need continued support after deployment.
- Defined monitoring scope
- Quality and cost reviews
- Incident support as agreed
- Scheduled improvements
Payment milestones. Projects are milestone-based. A typical structure is 50% at kickoff, 30% at accepted prototype, and 20% at handover. Actual terms are agreed in the contract and may vary by scope and procurement requirements.
Frequently asked questions
Before we get to work.
A few practical answers about scope, delivery, and what it takes to put AI into real business operations.
Start a conversation
Bring one costly workflow. We’ll map the path to a working system.
Tell us what your team is trying to automate, where the data lives, and what a successful outcome would look like. We’ll use that context to determine whether there is a sensible next step.
Tell us about your workflow
Share enough context for an initial conversation. No confidential data is needed in this form.