How ChargeGuru Uses Make to Cut System Migration Time from Months to Days

ChargeGuru merged two legacy EV charging platforms into a single system in 6 weeks using Make, compressing typical 3-month delivery cycles to 2-day turnarounds and enabling non-technical teams to build independently.

Impact

6 weeks

Migration completed

3 months → 2 days

Delivery cycle compression

Challenge

Two legacy EV platform systems needed to be merged into one in 6 weeks mid-summer, with no time for traditional development cycles.

Solution

Used Make's visual automation platform to coordinate five cross-functional teams through the migration, with scenarios serving as both implementation and documentation.

Tools & Technologies

What Leaders Say

We had such a tiny timeframe to make this happen. We said: Okay, we cannot code.

Laurent Salomon, Head of Engineering

Make is visual. Every team can understand what the other teams are building.

Laurent Salomon, Head of Engineering
Get the full story.

Sign up to read complete case studies, access detailed metrics, and unlock all use cases.

Full Story

ChargeGuru, an EV charging solutions provider operating across 8 markets, faced a seemingly impossible deadline: merge two legacy platforms — ChargeGuru and ZipPlug — into one unified system by August 15th, in the middle of summer vacation season. A traditional coding approach was off the table.

Engineering lead Laurent Salomon turned to Make's visual automation platform. Rather than writing code, five cross-functional teams — including non-technical staff from marketing, operations, and international markets — built and managed migration scenarios together using Make's visual interface.

The visual nature of Make's scenarios served double duty: it acted as both the implementation and the documentation, letting teams from different functions understand what others were building without handoff delays or translation gaps.

The migration completed on time. Beyond the deadline win, the project permanently shifted ChargeGuru's development culture. Delivery cycles that once took 3 months compressed to 2-day turnarounds, and non-technical teams gained the ability to build their own solutions independently.

Similar Cases

C
CustomGPT.ai
10,000+
paying customers served

CustomGPT.ai is a no-code RAG-as-a-Service platform enabling businesses to build domain-specific AI agents on their own data. By building its vector retrieval infrastructure on Pinecone, the company scaled to over 10,000 paying customers, stores 400+ million vectors, and delivers sub-20ms P50 query latency at 99.95%+ uptime. The result is a platform that earned the #1 ranking in a RAG accuracy benchmark, with Pinecone providing the foundation that let the engineering team focus entirely on product differentiation rather than infrastructure management.

TechnologyPPinecone
J
Jamf
70%+
employee adoption rate

Jamf, the leader in Apple enterprise management securing over 30 million devices for 75,000+ organizations worldwide, deployed the Moveworks AI Assistant (internally named Caspernicus) to transform employee support across IT, HR, Legal, and Facilities. Within the first month, 30% of employees adopted the assistant; today, more than 70% of Jamf’s workforce actively uses it to resolve requests that once took days in a matter of minutes. By meeting employees where they work in Slack, the platform automated routine tasks like password resets, software provisioning, and onboarding workflows, freeing IT to focus on higher-impact initiatives.

TechnologyMAMoveworks AI Assistant
TX
Terminal X
0.68 to 0.91
f1 retrieval accuracy improvement

Terminal X is a vertical AI platform for institutional investors that acts as a 24/7 research agent, processing millions of financial documents for hedge funds, asset managers, and private equity firms. By rebuilding its retrieval architecture on Pinecone’s vector database, Terminal X improved F1 retrieval accuracy from 0.68 to 0.91, cut average latency by over 35%, and doubled deployment velocity. Users now save approximately three hours per day, and investment memo preparation dropped from two days to half a day.

Financial ServicesTechnologyPPinecone
A
ASAPP
91%
first-call resolution rate

ASAPP is an AI-native customer service platform that orchestrates large language models to automate contact center interactions for enterprise clients. By deploying Anthropic’s Claude through Amazon Bedrock, ASAPP eliminated its homegrown PII redaction layer and reduced call escalations by up to 40%, while helping clients achieve a 91% first-call resolution rate. The platform now automates more than 90% of contact center interactions, with human agents freed to handle three times the volume of complex cases.

TechnologyCustomer Support TechnologyABAmazon BedrockC(Claude (via Amazon Bedrock)
D
Delphi
>100M
vectors stored

Delphi is an AI platform that enables coaches, creators, and experts to deploy interactive “Digital Minds”—always-on conversational agents trained on their unique content. Scaling from proof of concept to a commercial platform with thousands of customers required a vector database that could support millions of isolated namespaces, billions of vectors, and sub-second retrieval under variable load. Delphi selected Pinecone, achieving P95 query latency of 100ms and keeping retrieval under 30% of total response time—freeing the engineering team to build product rather than manage infrastructure.

TechnologyPPinecone
N
Notion
Millions
notion ai users reached

Notion, the connected workspace platform used by millions worldwide, integrated Cohere Rerank into its search pipeline to power Notion AI’s search accuracy across multilingual enterprise workspaces. Every search and Notion AI interaction now routes through Cohere Rerank, delivering dramatically improved relevance while cutting the cost and complexity of embedding-based retrieval for smaller workspaces.

TechnologyCRCohere Rerank
F
Fujitsu
World-class score
jglue benchmark performance

Fujitsu, the global IT and digital transformation company with 124,000 employees, partnered with Cohere to develop Takane — a state-of-the-art Japanese large language model built on the Cohere Command series. Designed for private deployment in regulated sectors such as finance, healthcare, and government, Takane delivers world-class performance on the JGLUE benchmark and is now integrated into Fujitsu’s AI service offerings and data intelligence platform.

TechnologyCCCohere Command
PA
Palo Alto Networks
351,000 hours
employee productivity hours saved

Palo Alto Networks, the global cybersecurity leader with nearly 15,000 employees, deployed Moveworks as an AI Assistant named Sheldon to deliver autonomous support across Slack, email, and ServiceNow. The platform resolves 4,000 IT and HR issues per month while saving 351,000 employee hours, enabling the company to scale its hybrid FLEXWORK model without adding headcount.

TechnologyMMoveworks