01
Specialised roles
Planner / researcher / executor / reviewer — each tuned.
Agentic AI Solutions
Multi-Agent Systems.
Multi-agent orchestration, production-grade.
Multi-agent orchestrations where specialised agents collaborate — planner, researcher, executor, reviewer. Shared memory, audit trail, RAG over private corpus, eval-driven design.
+24%
Accuracy
−38%
Cost per task
5×
Eval coverage
92%
Auto-decision
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 multi-agent systems
Multi-agent systems where specialised agents collaborate: planner / researcher / executor / reviewer. Shared memory, audit trail, RAG over private corpus. Eval-driven design and graph-level tracing.
Built where one monolithic agent would lose accuracy or be too expensive — split the work, share state, instrument every step.
Practice signalsSenior-ledWeekly demosCode review on every PRProduction on-call
01
+24%
Accuracy
Multi-agent vs monolith
02
−38%
Cost per task
Specialised agents
03
5×
Eval coverage
Per-node eval
04
92%
Auto-decision
Top orchestration
Business challenges we solve
What keeps teams shipping multi-agent systems.
Monolithic agents wandering on hard tasks
Reasoning errors compounding over long chains
Cost-per-task exploding on factored workflows
Audit trail across agent handoffs incomplete
Shared memory without scope collapses privacy
Eval coverage dropping with multi-agent complexity
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.
02
Shared memory
Scope-locked, lineage-tracked, audit-friendly.
03
Eval-driven
Graph-level eval, regression in CI per node.
Key features
What ships, by default in every engagement.
F·01
Planner agent
Decomposes tasks, routes to specialists, tracks progress.
F·02
Researcher agent
RAG over private corpus, citations, scope-locked.
F·03
Executor agent
Tool-using, idempotent, retries, audit trail.
F·04
Reviewer agent
Eval-driven grader, escalates on confidence drops.
F·05
Shared memory
Scope-locked, lineage-tracked, cache-friendly.
F·06
Tracing
Per-node tracing, replay, ROI dashboard.
Benefits & business outcomes
Numbers senior clients measure.
Top accuracy
Multi-agent vs monolith
+24%
Outcome · 01
Cost per task
v. monolith
−38%
Outcome · 02
Eval coverage
Per-node vs whole
5×
Outcome · 03
Development process
Senior squads. Tight loops. Code every day.
01
Week 1–2Workflow decomposition
Identify specialisation boundaries, shared state shape.
02
Week 3–4Agent design
Per-agent prompt + tool surface + eval.
03
Week 5–10Orchestration build
Shared memory, tracing, eval harness, grading.
04
OngoingOperate
Per-agent + graph ROI, monthly tuning.
Technologies we use
The stack we ship in production.
Layer · 01
Orchestration
LangGraph
TemporalRestate
Layer · 02
Models
ClaudeOpenAI
BedrockLayer · 03
Eval & Trace
Langfuse
Helicone
Braintrust
Industries we serve
Verticals where we've shipped, not where we dabble.
V·01
Research
Multi-source synthesis
Signal+24% Accuracy
V·02
Finance
Compliance, due diligence
Signal−38% Cost per task
V·03
Healthcare
Clinical intake + triage
Signal5× Eval coverage
V·04
Legal
Document review + drafting
Signal92% Auto-decision
V·05
Customer ops
Triage + research + reply
Signal+24% Accuracy
V·06
Engineering
Code review + tests + deploy
Signal−38% Cost per task
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
+24%
Accuracy
Signal
−38%
Cost per task
Signal
5×
Eval coverage
Signal
92%
Auto-decision
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.
FAQs
The questions we hear most.
If yours isn't here — ping us and we'll reply with specifics on your stack.
01When is multi-agent right?
Long workflows, specialisation boundaries, factored reasoning. For short workflows, monolith with good evals wins.
02How do agents share state?
Scope-locked shared memory with lineage tracking. Cache-friendly for read-heavy paths.
03Eval coverage at multi-agent scale?
Per-node evals + graph-level regression. We ship 200+ examples per node + 1000+ graph combinations.
04What about cost?
Per-agent cost dashboards, model fallback, kill switch on regressions. ROI per workflow tracked.
Related services
Other practices inside Agentic AI Solutions.
Free consultation
Ready to ship multi-agent systems?
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