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FAQ
Questions, answered straight
What we build, what it costs, how long it takes, and how to start — from a studio that builds and operates AI in production.
About GrahAI Systems
- What is GrahAI Systems?
- GrahAI Systems is a production-grade AI software studio that designs, builds and operates AI systems — AI agents, RAG (retrieval-augmented generation) systems, workflow automation and custom AI SaaS. We are engineer-led, based in Bengaluru, India, and we serve clients across India and the World.
- What makes GrahAI Systems different from other AI agencies?
- Most agencies only do client work. We also run four of our own AI products in production — GrahAI, OptionsGyani, AasanKhata and AgencyPitch — which means we live with the hard parts every day: latency, token cost, evals, payments, uptime and reliability. We bring that operating discipline to every client build, instead of handing over a demo that breaks under real traffic.
- Where is GrahAI Systems based and who do you work with?
- We are based in Bengaluru, India and work with founders, CTOs and product teams in India and internationally. Engagements are run remotely with clear scopes, fixed timelines and measurable success criteria.
- Do you only consult, or do you build and run the systems?
- We build and operate. A typical engagement is a fixed-scope build (4–10 weeks) followed by an optional operate-and-improve retainer where we monitor, tune and extend the system under an SLA — the same way we run our own products.
What we build
- What kinds of AI systems do you build?
- Four main types: AI agents that take real actions in your stack (calling APIs, updating records, completing multi-step work); RAG systems and private GPTs that answer over your own knowledge with citations and no hallucination; AI workflow automation that removes repetitive human steps between systems; and custom AI SaaS products built end to end.
- Can you integrate with our existing tools and stack?
- Yes. We integrate with your APIs, databases, CRMs, ERPs and SaaS tools rather than forcing a rip-and-replace, and we keep the AI layer decoupled so you are never locked in. We work across industry systems — from EHR/HL7 in healthcare to core banking and KYC in financial services to TMS/WMS in logistics.
- How do you stop the AI from hallucinating or making mistakes?
- Grounding, guardrails and evals. RAG answers are grounded in your data and cited; agents use confidence thresholds and human-approval gates for risky actions; and every release is gated by an automated evaluation suite plus step-level tracing so regressions are caught before they reach production.
- Which AI models do you use?
- We are model-agnostic and route per task for the best accuracy-to-cost ratio — frontier models like Claude, GPT and Gemini, plus open models where they fit. Model choice is an engineering decision we make and re-evaluate, not a fixed bet we lock you into.
Pricing & engagement
- How much does an AI project cost?
- Most production AI systems are a fixed-scope build in the ₹20L–₹50L / $20k–$60k range, depending on scope and integrations. We also offer productized engagements with published starting prices — for example an AI Customer Support Copilot from $6,000 and an AI Document Processing Platform from $15,000. You can get an instant scope and price at grahaisystems.com/start.
- How long does a typical build take?
- Productized engagements run 30–45 days. Custom production systems are typically a 4–10 week fixed-scope build. We define the timeline and success metrics up front so there are no surprises.
- How do we get started?
- Book a discovery call or use the instant scoping tool at grahaisystems.com/start. We scope a single high-value workflow, define success metrics, and return a fixed proposal you can approve — then you can track delivery from your own dashboard.
- Do you sign NDAs and handle data securely?
- Yes. We sign NDAs, scope data access to the minimum required, and design for the compliance posture of your industry. Sensitive data stays within boundaries you control wherever possible.
Still deciding?
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