Knowledge search and RAG
For fast retrieval from documents, FAQs, and internal knowledge bases.
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SYS,INIT v1.4.15
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FIRSTDATA.IR
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LLM integration, RAG, and automation to reduce repetitive work, improve accuracy, and speed up decisions.
▸Our AI products are shaped with a privacy-first mindset so language models, intelligent search, and semi-automated flows remain aligned with your data boundaries and operational policies.
user> summarize ticket #4821
sys> retrieving context… 3 docs
ai> Customer asked about SLA — draft ready.
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// ai product metrics
0+
AI flows
RAG, automation, assistants
0%
Privacy-first
Data boundary by design
0
Eval layers
Quality, cost, accuracy
0 wk
Fast pilot
Narrow, measurable use case
// use cases
For fast retrieval from documents, FAQs, and internal knowledge bases.
For summarization, classification, response drafting, and repetitive-task reduction.
For supporting sales, operations, support, or content management teams.
For suggestions, initial analysis, or user guidance in complex workflows.
// before / after
// live preview
user> summarize ticket #4821
sys> retrieving context… 3 docs
ai> Customer asked about SLA — draft ready.
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AI terminal with typing on prompt/response
// related samples
CRM, warehouse, and payment gateway connections with event queue and error monitoring.
→ Data exchange between systems runs without manual copy-paste.
Extract from legacy database, transform, and staged load with validation reports.
→ Migration completed with minimal downtime and staged rollback capability.
API layer on legacy software to connect a new web UI without full rewrite.
→ Users work in the new interface while the legacy core remains operational.
// features
// architecture
Question → retrieval → model → policy
// technology
Click a tag — why this stack?
// client signal“Support cut PDF search time significantly.”
// delivery process
We first define which friction AI should actually reduce.
Data sources, permissions, tone, and answer limits are prepared.
A prototype is tested against real scenarios and measured for quality.
Output quality, cost, accuracy, and privacy are monitored continuously.
// engagement tiers
Discovery + MVP
4–8 weeks
Fast start with a bounded, measurable scope
Full product
3–6 months
Complete product with integrations and admin
Enterprise
Long-term engagement
Scale, SLA, governance, and rollout
| Discovery + MVP | Full product | Enterprise | |
|---|---|---|---|
| RAG pilot | ✓ | ✓ | ✓ |
| Private model | — | Optional | ✓ |
Timelines are indicative — exact scope is set after discovery.
// related services
// product updates
Recent First Data releases — including product pages and panel capabilities.
// one-pager
Print/PDF version to share with stakeholders — summary, stack, and engagement path.
// faq
Privacy-first policy: data boundaries, anonymization, and private/VPC models when possible. Policy doc is approved before build.
// other products
// ready to start
Tell us about your project. We respond within one business day.
> status: online [OK] > reply: 1 biz day [OK] > slots: available [OK] > consult: free [OK]