Srishti GenAI is a generative AI and software engineering company helping businesses build AI agents, enterprise GenAI solutions, AI-powered workflow automation, RAG systems, and custom AI/ML applications. We work with businesses to design, develop, integrate, and deploy production-ready AI solutions across enterprise use cases.
Every engagement is led by our founder and solution architect, Ashok Bugude, who has 13+ years of enterprise engineering and consulting delivery. Clients work directly with the person designing the system, not through account handoffs.
We start with a thin pilot and written acceptance checks, measure against the operational metrics the business already tracks, and then roll out in phases. Systems are built to be usable by operations teams and governable by IT and compliance: retrieval grounded in approved content, guardrails, human approval where it matters, decision traceability and access controls.
Typical work includes AI agents that run multi-step workflows across CRM, ERP and internal tools; RAG and knowledge assistants over private documents; document extraction and classification; and LLM integration into existing applications. We serve clients in BFSI, healthcare, insurance, manufacturing, legal and logistics from Bengaluru, India.
New clients can start with a free two-week pilot, then continue hourly or with a dedicated engineer. Payment follows delivery.
Srishti GenAI is a generative AI and software engineering company helping businesses build AI agents, enterprise GenAI solutions, AI-powered workflow automation, RAG systems, and custom AI/ML applications. We work with businesses to design, develop, integrate, and deploy production-ready AI solutions across enterprise use cases.
Every engagement is led by our founder and solution architect, Ashok Bugude, who has 13+ years of enterprise engineering and consulting delivery. Clients work directly with the person designing the system, not through account handoffs.
We start with a thin pilot and written acceptance checks, measure against the operational metrics the business already tracks, and then roll out in phases. Systems are built to be usable by operations teams and governable by IT and compliance: retrieval grounded in approved content, guardrails, human approval where it matters, decision traceability and access controls.
Typical work includes AI agents that run multi-step workflows across CRM, ERP and internal tools; RAG and knowledge assistants over private documents; document extraction and classification; and LLM integration into existing applications. We serve clients in BFSI, healthcare, insurance, manufacturing, legal and logistics from Bengaluru, India.
New clients can start with a free two-week pilot, then continue hourly or with a dedicated engineer. Payment follows delivery.
Location and contacts
Major clients
Processes and approach
How do you gather and validate client requirements?
Every engagement starts with a discovery phase led by the solution architect: we review the workflow end to end with the people who run it, the systems it touches and the metrics it is judged on. Requirements are written up as a scoped use case with explicit acceptance checks, then validated in a thin pilot against real workload before any larger build is committed.
How do you ensure alignment with client goals and business strategy?
We tie each engagement to operational metrics the business already tracks, such as cycle time, resolution time, answer quality or manual processing effort, and agree the definition of done in writing before the build starts. Phased rollout means the decision to scale is made on measured results, not projections.
Which software development methodologies do you use (e.g., Agile, Waterfall, Scrum)?
Agile, iterative delivery: a thin pilot first, then short build iterations with working software shown early, followed by phased production rollout. Evaluation harnesses and acceptance checks are part of each iteration rather than a final testing phase.
How do you keep clients and stakeholders updated on project progress?
Clients work directly with the solution architect, with no account-manager layer. Progress is shared as working demos and written updates on scope, risks and next steps; for hourly work, hours are logged and reported before invoicing.
How frequently do you hold check-in meetings or status updates?
Weekly check-ins by default, with more frequent touchpoints during pilots and rollout; the cadence is agreed with each client at kickoff.
What quality assurance practices do you follow?
Evaluation sets built from real cases, regression testing of prompt, retrieval and model changes, guardrail and access-control testing, code review, and user acceptance testing with the operations team before each rollout phase.
How do you identify and manage project risks?
Risks are identified during discovery (data quality, access and security, compliance, integration, user adoption) and tracked in a written risk log. We reduce them by piloting on a narrow workflow first, keeping human approval on high-impact paths, and rolling out in phases with accuracy checks at each stage.
What kind of support or maintenance do you offer after delivery?
Post-launch support covers monitoring of quality and accuracy, prompt and retrieval tuning, model and dependency updates, bug fixes and enhancements, provided hourly or through a dedicated engineer on a monthly or yearly engagement.