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Agentic AI Solutions. Autonomous agents that ship work.

Production-grade AI agents — assistant copilots, multi-agent orchestrations, vertical workflows, and tool-using systems wired into your stack. Not demos. Not chatbots. Agents that move numbers and finish work.

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
01

Personal & executive copilots

Triage email, schedule meetings, summarise, draft — wired to your calendar, inbox, and docs.

Practice line
Talk to a lead
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
Technologies

The stack we ship in production.

Layer · 01

Models & Tooling

Claude / AnthropicClaude / Anthropic
OpenAIOpenAI
AWS BedrockAWS Bedrock
MCPMCP
Layer · 02

Retrieval & Memory

PineconePinecone
WeaviateWeaviate
QdrantQdrant
pgvectorpgvector
Layer · 03

Orchestration & Observability

LangGraphLangGraph
TemporalTemporal
HeliconeHelicone
LangfuseLangfuse
Sig · 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 1–2

Use-case triage

Map workflows to ROI, feasibility, risk. Pick 2–3 that move numbers in 90 days.

Exit criterion
Scored pipeline
02
Week 3–4

Agent design & evals

Tool surface, prompts, guardrails, eval suite of 200+ graded examples.

Exit criterion
Eval suite passes
03
Week 5–8

Build with shadow mode

Agent runs in shadow next to humans for 2 weeks, comparing decisions.

Exit criterion
≥85% parity
04
Ongoing

Handoff & 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 · 01

Agents that take real actions: read inbox, query DB, update CRM, file tickets, send approvals.

Multi-agent orchestration

AI · 02

Planner / executor / reviewer / researcher — coordinated, with shared memory and audit trail.

Long-running workflows

AI · 03

Durable agents that survive hours, days, weeks — Temporal-backed, resumable after restarts.

Domain fine-tunes

AI · 04

Fine-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
Pillar · 01

Vertical AI, not just LLMs

We build agents that actually move numbers — wired into your systems, your data, your workflows.

Pillar · 02

Ship in weeks, not quarters

Small senior squads, tight feedback loops, code-merge every day, demo every week.

Pillar · 03

Industrial-grade rigor

From PLCs to SOC2 — production safety, observability, and resilience baked in.

Pillar · 04

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