Who starts the work, who makes decisions, where it waits and who owns the outcome.
DISCOVER THE WORK. ENGINEER THE CHANGE.
AI that makes it
into the working day.
We map how your business actually runs, identify where AI earns its place, and engineer the workflows your team can use. From the first workshop to a supported production rollout.
Human-led consulting. Hands-on engineering. Visible costs.
FROM FRICTION TO FLOW ILLUSTRATIVE DELIVERY MAP
01Map the work02Price the change03Build & validate04Deploy & improve
People + systems + measurable outcomes
Start with a business ownerShow the assumptionsKeep people in controlMeasure real adoption
01 / UNDERSTAND BEFORE AUTOMATING
First, we learn
how the work gets done.
Interviews alone miss the workarounds. We combine team workshops, process walkthroughs and representative examples to map the agreed business areas end to end.
Applications, documents, access rules, integration options, data quality and missing context.
Frequency, handling time, rework, edge cases, failure consequences and escalation paths.
A workflow inventory, current-state maps, evidence gaps and agreed measures of success.
02 / PICK THE RIGHT FIRST WORKFLOW
Useful AI starts
with a specific job.
We rank opportunities by business value, feasibility, data readiness and risk. Some need AI. Some need a simpler integration. Some should stay with a person.
ILLUSTRATIVE WORKFLOW · NOT A CLIENT CASE STUDY
From incoming question to a grounded response.
The person stays responsible
What we measure
ILLUSTRATIVE SCENARIO / MANUFACTURING SAAS
Rasset.ai: look across the business, then start with one workflow.
For a manufacturing SaaS business such as Rasset.ai, the discovery scope could span the customer lifecycle and internal operations. Each opportunity needs its own owner, data check and business case.
Customer care & knowledgeSales research & CRMCustomer onboardingProduct feedback routingInternal reporting
Start by mapping support requests, sales handoffs and onboarding steps. Prioritize one bounded workflow, validate it with the team, and expand on evidence. This is an illustrative engagement scenario, not a statement of work completed for Rasset.ai or a claim of achieved results.
03 / MAKE THE BUSINESS CASE VISIBLE
Know what it takes.
Know what keeps costing.
Your proposal separates the initial build from the cost of running it. We document scope, assumptions, dependencies and exclusions before implementation begins.
Discover. Design. Deliver.
- Workflow discovery and prioritization
- Data preparation and integration work
- Architecture, application and AI engineering
- Evaluation, security review and acceptance testing
- Rollout, documentation and team training
Run. Review. Improve.
- Model usage and third-party licenses
- Hosting, storage, retrieval and monitoring
- Human review and exception handling
- Support, maintenance and regression testing
- Changes as data, models and workflows evolve
TRY A WORKFLOW BASELINE
How much work is in the workflow?
Use your own volumes to start the discussion. This estimates time available for reassignment, not guaranteed savings or a project quote.
66.7potential hours / monthBefore adoption, review and exception overhead.
The business case compares expected benefits with full lifecycle costs under low, base and high usage scenarios. Pricing and timelines are scoped after discovery; there is no universal deployment fee.
04 / ENGINEER FOR EVERYDAY USE
A pilot is a checkpoint.
Production is the job.
Design the system
Choose build, buy or a hybrid. Define data flows, permissions, integrations and human review. Use the simplest approach that meets the job.
Output: architecture + acceptance criteriaProve one workflow
Build a bounded pilot with representative test cases. Compare quality, latency and cost against the baseline, including difficult examples.
Gate: evidence supports a limited rolloutRelease with controls
Test access boundaries, unsafe inputs and failure paths. Add logging, budget limits, rollback and an explicit owner for incidents.
Gate: business + engineering acceptanceMake it stick
Train users, track adoption, monitor quality and review exceptions. Expand only after the workflow performs in daily use.
Output: runbook + improvement backlogUS + INDIA / ONE DELIVERY PLAN
Close to your business.
Connected through delivery.
Plan US and India engineering around the workflow, your stakeholders and your operating hours. The proposal specifies who does what, where work happens and how decisions move between teams.
Team allocation, onsite needs, working-hour overlap and data-access locations are agreed in the statement of work.
USBusiness alignment
Discovery & architecture
Stakeholder reviews
Discovery & architecture
Stakeholder reviews
Shared backlog · demos · decisions
INDIAEngineering & integration
Testing & release preparation
Ongoing improvement
Testing & release preparation
Ongoing improvement
One accountable delivery lead. Clear handoffs. Visible progress.
TRANSPARENCY, BUILT INTO THE ENGAGEMENT
You can see the work.
And take ownership of it.
Each engagement defines the deliverables, access model and handover terms before work begins.
Prioritized workflows, cost assumptions, sequencing, dependencies and a reason for each recommendation.
A shared backlog, working demos, milestone reviews, risks and decisions recorded as the work progresses.
Test results, quality checks, usage and cost reporting, failure modes and a documented rollout decision.
Agreed source-code and IP terms, configuration documentation, runbooks, training and defined support boundaries.
Before we start.
Do we need AI in every workflow?
No. We may recommend process changes, rules-based automation or an existing product. The objective is a better workflow, not more AI.
Can you work with our existing systems?
Discovery checks API access, export options, identity, licensing and data quality. The architecture and quote identify supported integrations and any dependencies before committing to delivery.
Which models and cloud platforms do you use?
Selection follows your quality, data, latency and cost requirements. We evaluate available options against representative tasks and document the chosen stack rather than prescribing one vendor upfront.
How do you handle sensitive data?
Agree data classification, permitted regions, retention, provider terms and least-privilege access before connecting systems. Human review, audit trails and escalation are designed around the workflow’s risk.
What does the first engagement deliver?
A scoped workflow inventory, prioritized opportunity assessment, architecture direction, cost model and delivery plan. Discovery scope and deliverables are agreed before kickoff; implementation is a separate decision.
START WITH THE WORK THAT NEEDS TO CHANGE.
Bring the bottleneck.
We’ll map the way forward.
Bring a workflow, the systems involved and the outcome you want. We’ll discuss a discovery scope and what it would take to implement.
Discuss AI deployment ↗