We implement AI that survives production—not slide-deck demos. Document extraction, intelligent search, demand forecasting, and agent workflows wired into ERP, CRM, and support tools you already run.
DigiOpera focuses on use cases finance can track: hours saved on invoice processing, deflection rate on tier-1 support, or forecast accuracy for inventory planners. We audit data readiness, pick models appropriate to volume and latency, and deploy with human-in-the-loop safeguards.
OCR plus LLM extraction for invoices, contracts, and KYC packets.
Support bots grounded in your knowledge base with escalation paths.
Demand, churn, and maintenance signals fed into dashboards.
Models run in your VPC or approved cloud regions. PII is masked, prompts are logged, and outputs are validated before posting to ERP or customer records.
We operationalise MLOps: monitoring drift, retraining schedules, and cost caps on token usage so AI spend stays predictable at scale.
Discuss AI Software Development for Real Business Outcomes with a senior consultant. We will outline scope, timeline, and investment—without a hard sell.
Workshops for product and ops teams explain what AI can and cannot do, reducing hype-driven requests and focusing backlog on high-impact automations.
Effective pilots define measurable outcomes upfront: e.g. 85% field accuracy on invoice line items or 30% tier-1 ticket deflection. Typical document-AI pilots run 6–10 weeks at USD 25k–55k including evaluation harness and human review UI.
We benchmark OpenAI, Azure OpenAI, Anthropic, and open-weight models on your redacted samples. PII masking, regional hosting, prompt logging, and retention policies are documented before production traffic.
Not always—RAG and pre-trained models solve many document and support tasks with moderate historical data.
We are model-agnostic and recommend based on data residency, cost, and accuracy benchmarks on your samples.
Retrieval grounding, citation links, confidence thresholds, and human handoff keep answers tied to approved content.
Never without explicit consent. Enterprise API terms and private deployments keep your data isolated.
Focused pilots—such as invoice extraction for one vendor format—often land in a mid five-figure USD range over 6–10 weeks.
RAG first for knowledge bases and support; fine-tune when proprietary terminology or format compliance needs tighter control.
Yes for suitable models—GPU sizing and latency trade-offs are part of the architecture proposal.
Document extraction, support triage, and demand forecasting tied to existing data warehouses—avoid open-ended chatbot pilots without KPIs.
Role-based access, audit logs, and optional on-prem or VPC deployment for sensitive datasets are defined in the architecture phase.
Government-recognised registrations and verifiable corporate identifiers.
Registered office: 3rd Floor, Landmark Cyber Park, Sector 67, Gurugram, Haryana 122102, India
Send a sample workflow—we will suggest a pilot scope, stack, and success metrics.
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