The work between
your systems
automated.
Nava deploys AI workflows that handle communications, process documents, retrieve information and update your existing systems, with people in control of the decisions that matter.
Built for service businesses running complex operational workflows.
Start with one high-cost workflow. Prove the outcome. Expand from there.
Most businesses already have the software. The expensive part is the work between it.
Employees still read messages, open attachments, search for records, copy information between systems, draft responses and decide what happens next. Nava operates as a layer across that sequence, running it as a governed AI workflow inside your existing stack.
Different workflows. Shared infrastructure.
Every workflow reuses the same integrations, permissions, operational context, components and governance. Once the layer is in place, adding the next workflow is configuration rather than a new build.
The first workflow establishes the foundation for the next.
One operating layer, configured for the way your industry works.
The operational pattern is the same everywhere: information arrives, documents are checked, records are found and updated, and someone decides what happens next. Only the systems and rules change.
Reduce the administrative load around every client engagement.
Client information arrives by email, sits in attachments and has to be chased, checked and re-entered into practice-management systems before any specialist work begins.
Less time gathering and moving information. More time applying specialist judgement.
- 01Client onboarding and information collection
- 02Inbox triage and request classification
- 03Tax-document extraction and validation
- 04Automated chasing of missing information
- 05Retrieval of client records and prior correspondence
- 06Drafting routine client communications
- 07Updating CRM and practice-management systems
Nava is configured around the practice-management, CRM and document systems your firm already runs on. The same operating layer is configured against the reality of your specific systems, teams and controls.
Start with one expensive workflow. Prove the outcome. Expand from there.
Identify
Select the workflow with the clearest operational value.
- Understand the current process
- Map systems, handoffs and exceptions
- Establish a measurable baseline
- Define the desired operational outcome
Configure
Configure Nava around the organisation's existing operation.
- Connect relevant systems and data
- Configure workflow logic and permissions
- Use real operational examples
- Establish human-review thresholds
Prove
Measure the workflow against the existing process.
- Time saved
- Response times
- Processing capacity
- Accuracy and exception rates
Expand
Extend the same operating layer into adjacent workflows.
- Reuse existing integrations
- Reuse permissions and operational context
- Add workflow modules and actions
- Increase capacity without equivalent headcount growth
AI that fits your business... not the other way around.
Existing systems
Nava works across the tools your teams already use rather than requiring a complete platform replacement.
Human control
Approvals, escalation rules and confidence thresholds keep people in control of consequential decisions.
Traceability
Maintain a clear record of the information used, actions taken and human review involved.
Deployment flexibility
Deploy around the organisation's cloud, security, data and governance requirements.
Operational measurement
Measure success through processing time, capacity, response speed, accuracy and exception rates, not AI usage statistics.
Reusable architecture
The first workflow establishes integrations, context and controls that can be reused across future deployments.
Specific hosting, security and governance requirements are agreed before deployment.
Built by operators who have deployed AI into complex environments.
Cole Dorrestein
CEO- Exited AI founder, having built and shipped an AI product end to end.
- ex-Quant, part of the founding digital assets team at Marex Solutions.
- MSc Strategic Marketing and Machine Learning at Imperial College Business School.
- Focuses on where AI creates measurable operational value, identifying the highest-impact bottlenecks and the workflows worth deploying against them.
Ansh Arora
CTO- ex-Palantir, led a team of Forward Deployed Engineers inside complex operational environments.
- Built software for the National Fraud Intelligence Bureau; secure code that touched every financial crime report in the UK.
- MSc Machine Learning from Imperial College London.
- Builds production AI systems across AWS and Microsoft Azure, with the integrations, permissions and controls enterprises require.
Start with one workflow.
Tell us where your team loses the most time moving information between inboxes, documents and core systems. We will map that workflow and define the operational outcome worth deploying against.
We will assess the process, its potential operational impact and whether it is a strong fit for Nava.