01
Personal & executive copilots
Triage email, schedule meetings, summarise, draft — wired to your calendar, inbox, and docs.
Practice line
Talk to a lead
Autonomous agents that ship work.
AI agents that finish the work.
Production-grade AI agents from Abstriq, an agentic AI company in India. Assistant copilots, multi-agent orchestrations, vertical workflows, and tool-using systems wired into your stack — built by senior AI engineers from our Noida office.
200+
Evals per agent
92%
Highest auto-decision
0
P0 data leaks
−41%
Cost-per-task peak
Trusted by enterprises
Aaj Tak◆
Times of India◆
BJP◆
Beyond Reach Premiere League◆
Red Fm◆
Wellness Fuel◆
Junior Cricket Championship◆
ON Energy◆
ORYZO AI◆
Nursing Sarathi◆
Baatshala Ai◆
The Traffic People◆
Aaj Tak◆
Times of India◆
BJP◆
Beyond Reach Premiere League◆
Red Fm◆
Wellness Fuel◆
Junior Cricket Championship◆
ON Energy◆
ORYZO AI◆
Nursing Sarathi◆
Baatshala Ai◆
The Traffic People◆
Aaj Tak◆
Times of India◆
BJP◆
Beyond Reach Premiere League◆
Red Fm◆
Wellness Fuel◆
Junior Cricket Championship◆
ON Energy◆
ORYZO AI◆
Nursing Sarathi◆
Baatshala Ai◆
The Traffic People◆
Service overview
Vertical AI agents wired into your real systems.
We build agents that read your inbox, query your DB, update your CRM, and file tickets — with the audit trail and guardrails you need to put them in front of a real customer. Generic LLM calls are the easy part. The hard part is integrating them with your auth, your data, and your on-call rotation. That's what we do.
Practice signalsSenior-ledWeekly demosCode review on every PRProduction on-call
01
92%
Auto-decision rate
Insurance claims triage agent
02
−71%
Cycle-time cut
Insurance claim cycle, 11d → 3.2d
03
−41%
Support cost / order
Conversational commerce agent
04
+19%
Repeat-purchase
Two quarters after agent launch
Problems we solve
What keeps your agentic ai solutions team stuck.
POC agents that never survive first contact with real customers
LLM spend headless and growing — no per-agent ROI
Hallucinations & data leaks blocking enterprise rollout
Agents that can't take actions — they only write drafts
Knowledge bases that go stale the day after they're built
Internal teams stuck doing work that agents should be doing
Our solutions
Six senior-led practice lines.
Every solution is engineered by a senior lead with clear ownership, measurable outcomes, and the kind of code-review culture you'd build internally if you had a year to do it.
Metric · 01
200+
Evals per agent
Metric · 02
92%
Highest auto-decision
Metric · 03
0
P0 data leaks
Metric · 04
−41%
Cost-per-task peak
02
Enterprise copilots
Domain agents that read your wiki, query your DB, file tickets, answer employee questions safely.
Practice line
Talk to a lead
03
Chat & voice agents
Conversational agents across chat, voice, and email — with quality monitoring and human handoff.
Practice line
Talk to a lead
04
Workflow agents
Long-running agents that close tickets, run reconciliations, and execute multi-step ops with approval gates.
Practice line
Talk to a lead
05
Multi-agent systems
Orchestrations where specialised agents collaborate — planner, researcher, executor, reviewer.
Practice line
Talk to a lead
06
Knowledge & research agents
RAG over your private corpus with hybrid retrieval, citations, and continuous re-indexing.
Practice line
Talk to a lead
Service categories
10 sub-services under one roof.
Pick the card that maps to your problem. Every entry is staffed by a senior practice lead — no shared junior pool, no bait-and-switch.
01
Personal AI Assistants
Open sub-service
02
Enterprise AI Agents
Open sub-service
03
Chat & Voice Agents
Open sub-service
04
Autonomous Workflow Agents
Open sub-service
05
Multi-Agent Systems
Open sub-service
06
Knowledge & Research Agents
Open sub-service
07
E-commerce & Retail AI Agents
Open sub-service
08
Finance & FinTech AI Agents
Open sub-service
09
Healthcare & MedTech Agents
Open sub-service
10
Education & Learning Agents
Open sub-service
Technologies
The stack we ship in production.
Layer · 01
Models & Tooling
Claude / AnthropicOpenAI
AWS Bedrock
MCPLayer · 02
Retrieval & Memory
PineconeWeaviateQdrant
pgvectorLayer · 03
Orchestration & Observability
LangGraph
Temporal
HeliconeLangfuseSig · 01
Evals per agent
200+
Sig · 02
Highest auto-decision
92%
Sig · 03
P0 data leaks
0
Sig · 04
Cost-per-task peak
−41%
Development process
Senior squads. Tight loops. Code every day.
01
Week 1–2Use-case triage
Map workflows to ROI, feasibility, risk. Pick 2–3 that move numbers in 90 days.
Exit criterion
Scored pipeline
02
Week 3–4Agent design & evals
Tool surface, prompts, guardrails, eval suite of 200+ graded examples.
Exit criterion
Eval suite passes
03
Week 5–8Build with shadow mode
Agent runs in shadow next to humans for 2 weeks, comparing decisions.
Exit criterion
≥85% parity
04
OngoingHandoff & operate
Kill switch, audit log, eval dashboard, on-call runbook, monthly tuning.
Exit criterion
Live in production
Key features
What ships, by default in every engagement.
F·01
Eval-first delivery
Every agent ships with a graded eval dataset of 200+ examples — regression in CI before merge.
F·02
Guardrails & policy
PII redaction, jailbreak detection, per-tenant policy, scope-limited tools, human-in-the-loop confirmations.
F·03
Tool surface as code
Tools defined with typed schemas, OAuth-scoped access, idempotency keys, retry semantics.
F·04
Per-agent ROI dashboard
Cost per task, success rate, escalation rate, time-saved — all on one screen, refreshable monthly.
F·05
Tracing & replay
OpenTelemetry-traced every step, replay any production conversation with the exact model output.
F·06
SOC2 / GDPR posture
Zero-retention endpoints where required, audit logging, region-pinned inference, BAA-ready.
AI capabilities
Agentic AI baked into the practice.
AI isn't a separate service we sell on top — it's the engine that accelerates every engagement. Eval harnesses, agent surfaces, RAG-on-your-corpus as defaults.
92%
Auto-decision rate
−71%
Cycle-time cut
−41%
Support cost / order
+19%
Repeat-purchase
Tool-using agents
AI · 01Agents that take real actions: read inbox, query DB, update CRM, file tickets, send approvals.
Multi-agent orchestration
AI · 02Planner / executor / reviewer / researcher — coordinated, with shared memory and audit trail.
Long-running workflows
AI · 03Durable agents that survive hours, days, weeks — Temporal-backed, resumable after restarts.
Domain fine-tunes
AI · 04Fine-tuned small models on your private data when latency / cost / accuracy demand it.
Industries
Verticals where we've shipped, not where we dabble.
V·01
E-commerce & Retail
Conversational commerce, merchandising, returns, support
Signal6 Verticals shipped
V·02
Finance & FinTech
Reconciliation, advisory, KYC ops, collections
Signal92% Auto-decision peak
V·03
Healthcare
Intake triage, claims, prior-auth, care coordination
Signal−71% Best cycle-time cut
V·04
Education
Tutoring, grading, enrolment advising, content authoring
Signal−41% Support cost / order
V·05
Professional services
Document review, drafting, scheduling, research
Signal6 Verticals shipped
V·06
Manufacturing
Field ops, scheduling, supplier coordination
Signal92% Auto-decision peak
Vertical · 01
6
Verticals shipped
Vertical · 02
92%
Auto-decision peak
Vertical · 03
−71%
Best cycle-time cut
Vertical · 04
−41%
Support cost / order
Why Abstriq
Built for teams who ship fast in production.
We're not a body shop or a freelance marketplace. We run a senior-heavy engineering org with clear practice leads, real code review, and real on-call coverage.
Signal · 01
6
Verticals shipped
Signal · 02
92%
Auto-decision peak
Signal · 03
−71%
Best cycle-time cut
Signal · 04
−41%
Support cost / order
Vertical AI, not just LLMs
We build agents that actually move numbers — wired into your systems, your data, your workflows.
Ship in weeks, not quarters
Small senior squads, tight feedback loops, code-merge every day, demo every week.
Industrial-grade rigor
From PLCs to SOC2 — production safety, observability, and resilience baked in.
One team across four worlds
Web, mobile, AI, and industrial under one roof — no vendor ping-pong.
Testimonials
What clients say after the engagement.
“They shipped an agent that closes its own tickets. We measure cost, success rate, and time-saved monthly — it's been cash-flow positive from month two.”
SL
Sara Lindqvist
Head of Operations · Mid-stage Insurer
“The eval harness alone is worth the engagement. We finally know what 'good' means before it ships, not after a customer complains.”
RI
Rohan Iyer
CTO · Series-C D2C Brand
FAQs
The questions we hear most.
If yours isn't here — ping us and we'll reply with specifics on your stack.
01Will the agent replace our team or just take the worst 30% off their plate?
We design for the latter. Agents that handle the long tail of repetitive work, with humans on the edge cases — measurable, defensible ROI, no org-chart disruption.
02What evals do you run before declaring an agent production-ready?
Minimum 200 graded examples drawn from real traffic, plus a shadow-mode run simulating 1k decisions. We will not ship an agent that doesn't clear both.
03How do you control hallucination and data leakage?
Retrieval scope-locked to your corpus, citation required above 0.7 confidence, PII redaction, per-tenant policy via Cedar / OPA, kill switch, zero-retention endpoints where required.
04What's a realistic timeline to first production agent?
Six weeks for a single workflow agent with eval harness in shadow mode. Eight to twelve weeks for multi-agent orchestrations.
Contact CTA
Ready to ship agentic ai solutions?
Tell us the problem and we'll send you a working proposal in under 48 hours — typically with a walkable proof-of-concept. Reply within 24h, NDA-friendly by default.
Reply within 24h
NDA-friendly by default
Senior-led
India — global clients