What We Provide
Fast-turnaround POCs for internal orcustomer-facing use cases
Targo Timeline: Pilot proof-of-concept in ~2–3 weeks(build and demo a sample data flow); full pipeline in 4–8 weeks.
Upsell: Ongoing data engineering retainer, data warehousing, or managed database services.
Includes data discovery data quality review, and building simple ingestion pipelines or feature stores. Good data pipelines are prerequisite for any AI.
Build functional AI demos that simulate real user experiences — from scheduling automation to generating images or summaries. All powered by your use-case.
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Build functional AI demos that simulate real user experiences — from scheduling automation to generating images or summaries. All powered by your use-case.
We don’t just imagine — we code. Get actual Python-based AI logic and working APIs as part of your POC. What you see is what will scale.
class AutomationTrigger:
def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."
def get_status(self):
return f"Status: {self.status}"
class AutomationTrigger:
def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."
def get_status(self):
return f"Status: {self.status}"
We don’t just imagine — we code. Get actual Python-based AI logic and working APIs as part of your POC. What you see is what will scale.
Unlock tailored AI Strategy at your pace
Basic
Ideal for consultation
30-min discovery call
Roadmap templates
Readiness checklist
Premium
/month
Ideal for those with minor to moderate use.
1:1 strategy session
Full roadmap & 3 use cases
Assessment & support
Ultimate
Tailored for swift expansion
Full-day workshop
Dept.-wise roadmap
Strategy check-ins
Let's build your success together.