AI & DATA / AI IMPLEMENTATION
Production AI systems
Useful AI.
Part of everyday work.
Turn validated technology into a usable system, including interfaces, permissions, integrations, records and monitoring.
- FOR
- Companies ready to put a defined AI approach into operation
- PHASE
- Implementation
- ESTIMATE
- Proposed individually after confirming scope
PARTNERSHIP
Snowflake partner
TECHNOLOGY
BigQuery
Cloud Run
Cloud SQL
Google Cloud
BigQueryCloud RunCloud SQLFROM WORKFLOW TO DELIVERABLES
How we work ↗- 01Agree on requirements and acceptance
- 02Design and implementation
- 03Test real operational scenarios
- 04Rollout and operational handover
01 SCOPE & DELIVERABLES
What this engagement delivers.
Use the following as a starting point to agree on deliverables for your workflow and requirements.
Business interfaces, AI functionality and integrations
Test results and rollout procedures
Operating documentation
If available,
bring these to the conversation.
- Adoption strategy or PoC findings
- Existing system integration constraints
- User volumes and information-management requirements
Incomplete documentation is fine. Start by describing your current situation.
02 PROJECT FLOW
A visible path to delivery.
- 01
Agree on requirements and acceptance
- 02
Design and implementation
- 03
Test real operational scenarios
- 04
Rollout and operational handover
Decision point
Confirm acceptance criteria before rollout, then separately define maintenance and improvement scope.
DESIGN / VALIDATE / OPERATE
Connect AI outputs to approval and operational work.
Implement ingestion, retrieval, generation, evidence display and review as a connected workflow. Distinguish permissions for displaying an answer from those for updating operational systems.
What this stage establishes
Retain evaluation cases for source updates, role changes and external service changes. Agree acceptance with operating users, including latency and failure messages.
Evaluate representative and exceptional cases separately from the data used during development.
Make it possible to trace answers and metrics to source records and their update state.
Define handling for incorrect answers, unauthorized retrieval and failed operations, with a manual fallback.
03 ENGAGEMENT
Define the scope before starting.
Cost, timing and terms are proposed after confirming scope and the team required.
A CLEAR FIRST STEP
The scope you need.
An informed decision to start.
Tell us about your objectives and current situation.
We will propose a clear scope, deliverables and approach.
- 01
Contact
Start with your current situation and challenges, even before requirements are defined.
- 02
Review scope, deliverables and estimates
Review work, cost, timing and exclusions. Additional work is discussed before it begins.
- 03
Start with the agreed phase
Confirm the terms before starting. Subsequent phases depend on results and business needs.
04 QUESTIONS
Start with your questions.
Q.Can we commission only a PoC?＋
Yes. We agree on the validation scope, evaluation method and deliverables. The production decision can follow the results.
Q.Can we start if our data is not organized?＋
We first review data locations and formats. If preparation is needed, we propose that scope separately from AI development.
Q.Do we need both Snowflake and Google Cloud?＋
No. We assess the existing environment, volumes, access needs and operating structure to choose an appropriate architecture.