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Agentic AI Solutions

Knowledge & Research Agents.
RAG agents that cite, not hallucinate.

RAG agents over your private corpus — wiki, Confluence, drive, Notion, DB. Hybrid retrieval, citations, re-indexing on edit, scope-locked per tenant.

94%
Citation rate
<6 hrs
Drift to fresh
100%
Tenant isolation
+19pp
Accuracy
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

Engineering knowledge & research agents

Knowledge agents that answer employee / customer questions over your wiki, Confluence, drive, Notion, DB — with citations, recency awareness, scope-locked per tenant. Continuous re-indexing on edit so answers don't go stale the day after the agent is built.

Hybrid retrieval: lexical + semantic + reranking. Above-threshold confidence requires citation; below-threshold escalates to human.

Practice signalsSenior-ledWeekly demosCode review on every PRProduction on-call
01
94%
Citation rate
Top tier
02
<6 hrs
Drift to fresh
Webhook-driven
03
100%
Tenant isolation
Scope-locked
04
+19pp
Accuracy
Hybrid vs vector-only
Business challenges we solve

What keeps teams shipping knowledge & research agents.

RAG that hallucinates because drift > accuracy

Knowledge bases going stale on day two

Answers that don't cite, so users don't trust them

Shared knowledge bases leaking across tenants

Latency budgets impossible with naive RAG

No eval coverage on factual recall

Why choose this service

Three senior-led practice lines.

Outcome-anchored, owned by a practice lead with clear accountability, weekly demos, and the kind of code review culture you'd build internally if you had a year.

01

Hybrid retrieval

Lexical + semantic + reranking, with citations.

02

Continuous indexing

Webhook-driven re-indexing on edit.

03

Per-tenant scope

Scope-locked retrieval, audit trail.

Key features

What ships, by default in every engagement.

F·01

Corpus ingestion

Wiki, drive, Notion, Confluence, DB, custom sources.

F·02

Hybrid retrieval

BM25 + vector + reranking, with citations.

F·03

Recency logic

Re-index on edit, decay-to-fresh, time pin.

F·04

Citations

Required above 0.7 confidence; live SERP preview.

F·05

Per-tenant scope

Scope-locked retrieval, RBAC bridge.

F·06

Eval harness

Factual recall + drift, regression in CI.

Benefits & business outcomes

Numbers senior clients measure.

Citation rate

Top tier

94%
Outcome · 01

Drift to fresh

On edit, hours not weeks

<6 hrs
Outcome · 02

Tenant isolation

Scope-locked retrieval

100%
Outcome · 03
Development process

Senior squads. Tight loops. Code every day.

01
Week 1

Corpus audit

Map sources, ownership, refresh cadence.

02
Week 2–3

Ingestion + retrieval

Hybrid indexing, score-per-source, refresh hooks.

03
Week 4–6

Build + eval

Eval suite, citations, scope-locked per tenant.

04
Ongoing

Operate

Drift dashboard, refresh hooks, monthly tuning.

Technologies we use

The stack we ship in production.

Layer · 01

Retrieval

PineconePinecone
Weaviate
Qdrant
pgvector
Layer · 02

Sources

Notion
Confluence
Drive
S3
Layer · 03

Eval

Braintrust
Langfuse
Custom factual eval
Industries we serve

Verticals where we've shipped, not where we dabble.

V·01

Enterprise IT

Wiki, runbooks

Signal94% Citation rate
V·02

Legal

Case law, contracts

Signal<6 hrs Drift to fresh
V·03

Healthcare

Clinical, policy, formulary

Signal100% Tenant isolation
V·04

Manufacturing

Manuals, SOPs

Signal+19pp Accuracy
V·05

Education

Curriculum, research

Signal94% Citation rate
V·06

Finance

Compliance, regulations

Signal<6 hrs Drift to fresh
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
94%
Citation rate
Signal
<6 hrs
Drift to fresh
Signal
100%
Tenant isolation
Signal
+19pp
Accuracy
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.

FAQs

The questions we hear most.

If yours isn't here — ping us and we'll reply with specifics on your stack.

01Hybrid vs vector-only retrieval?
Hybrid (BM25 + vector + rerank) wins on factual recall. Vector-only hallucinates on entity names, codes, IDs.
02How fast does the index refresh on edit?
Webhook-driven within minutes. Recency decay logic in retrieval — fresh wins over stale at equal relevance.
03Multi-tenant scope?
Per-tenant retrieval scopes, RBAC bridge, audit trail. No leakage between tenants even within shared storage.
04Eval coverage?
Factual recall suite with ground-truth answers, monthly eval runs, regression in CI before merge.
Free consultation

Ready to ship knowledge & research agents?

Tell us the problem — proposal in under 48 hours. NDA-friendly by default, senior-led, and we typically walk you through a proof-of-concept before the engagement closes.

Reply in 24hNDA-friendlySenior-ledProduction on-call

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